Sweet trip to Boko and Borobudur.....

Distribusi Frekuensi 2

Describing Data:
Frequency Distributions
and Graphic Presentation
Chapter 2
GOALS
When you have completed this chapter, you will be able to:
• Organize raw data into a frequency distribution
• Produce a histogram, a frequency polygon, and a cumulative
frequency polygon from quantitative data
• Develop and interpret a stem-and-leaf display
• Present qualitative data using such graphical techniques
as a clustered bar chart, a stacked bar chart, and a pie chart
• Detect graphic deceptions and use a graph to present data
with clarity, precision, and efficiency.
1498
1548
1598
1648
1698
1748
1898
1948
2000
Florence Nightingale (1820–1910)
The tendency to graphically represent information seems to be
one of the basic human instincts. As such, identification of the
oldest such representation is an elusive- task, the earliest
known being the map of Konyo, Turkey, dated 6200 B.C. The earliest
known bar chart is the one by Bishop N. Oresme (1350).
Most of the modern forms of statistical graphic techniques were
invented between 1780 and 1940. In 1786, William Playfair used
time-series graphs to depict the amount of import and export to and
from England, and in 1801, he published a pie chart to show graphically
that the British paid more tax than other countries. The first
stacked bar chart, cumulative frequency polygon and histogram were published, respectively,
by A. Humboldt (1811), J.B.J. Fourier (1821), and A.M. Guerry (1833). The same
period saw development of non-trivial applications of these techniques to real-world problems.
One of the most significant contributors in this regard was the lady with a lamp,
Florence Nightingale.
Florence Nightingale was born in Florence, Italy in 1820, but was raised mostly in
Derbyshire, England. In spite of resistance from society and her mother, her father educated
her in Greek, Latin, French, German, Italian, history, philosophy, and, her favourite
subject, mathematics.
When she was 17 years old, Florence had a spiritual experience. She felt herself called
by God to His service. Since that time, she made up her mind to dedicate her life to some
social cause. She refused to marry several suitors and at the age of twenty-five, stunned
her parents by informing them that she had decided to be a nurse, a profession considered
low class at that time.
During the 1854 British war in Crimea, stirred by the reports of primitive sanitation
methods at the British barracks’ hospital, she volunteered her services, and set out to
Scutari, Turkey with a group of 38 nurses. Here, mainly by improving the sanitary conditions
and nursing methods, she managed to bring down the mortality rate at the hospital
from 42.7 percent to about 2 percent.
On her return to England after the war as a national hero, she dedicated herself to
the task of improving the sanitation, and quality of nursing in military hospitals. In this,
she encountered strong opposition from the establishment. But with the support of Queen
Victoria, and more importantly, with shrewd use of graphic methods (such as stacked bar
charts and a new type of polar bar chart that she developed on her own), she succeeded
in bringing forth reforms. She was one of the first to use graphical methods in a prescriptive,
rather that merely a descriptive way, to bring about social reform.
Over the subsequent 20 years, she applied statistical methods to civilian hospitals,
midwifery, Indian public health, and colonial schools. She briefly served as an adviser to
the British war office on medical care in Canada. Her mathematical activities included
determining “the average speed of transport by sledge,” and “the time to transport the
sick over immense distances in Canada.”
With her statistical analysis, she revolutionized the idea that social phenomena could
be objectively measured and subjected to mathematical analyses. Karl Pearson acknowledged
her as “prophetess” in the development of applied statistics.
Nightingale held strong opinions on women’s rights, and fought for the removal of
restrictions that prevented women from having careers. In 1907 she became the first
woman to receive the Order of Merit, an order established by King Edward VII for meritorious
service.
34 Chapter Two
Introduction
Rob Whitner is the owner of Whitner Pontiac. Rob’s father founded the dealership in
1964, and for more than 30 years they sold exclusively Pontiacs. In the early 1990s
Rob’s father’s health began to fail, and Rob took over more of the dealership’s day-to-day
operations. At the same time, the automobile business began to change—dealers began
to sell vehicles from several manufacturers—and Rob was faced with some major decisions.
The first came when another local dealer, who handled Volvos, Saabs, and
Volkswagens, approached Rob about purchasing his dealership. After considerable
thought and analysis, Rob made the purchase. More recently, the local Jeep Eagle dealership
got into difficulty and Rob bought it out. So now, on the same lot, Rob sells the
complete line of Pontiacs; the expensive Volvos and Saabs; Volkswagens; and Chrysler
products including the popular Jeep line. Whitner Pontiac employs 83 people, including
23 full-time salespeople. Because of the diverse product line, there is quite a bit of variation
in the selling price of the vehicles. A top-of-the-line Volvo sells for more than twice
the price of a Pontiac Grand Am. Rob would like to develop some charts and graphs that
he could review monthly to see where the selling prices tend to cluster, to see the variation
in the selling prices, and to note any trends. In this chapter we present techniques
that will be useful to Rob or someone like him in managing his business.
2.1 Constructing a Frequency
Distribution of Quantitative Data
Recall from Chapter 1 that we refer to techniques used to describe a set of data as descriptive
statistics. To put it another way, we use descriptive statistics to organize data
in various ways to point out where the data values tend to concentrate and to help
distinguish the largest and the smallest values. The first method we use to describe a
set of data is a frequency distribution. Here our goal is to summarize the data in a table
that reveals the shape of the data.
Frequency distribution A grouping of data into non-overlapping classes
(mutually exclusive classes or categories) showing the number of observations
in each class. The range of classes includes all values in the data set (collectively
exhaustive categories).
How do we develop a frequency distribution? The first step is to tally the data
into a table that shows the classes and the number of observations in each class.
The steps in constructing a frequency distribution are best described using an
example. Remember that our goal is to make a table that will quickly reveal the
shape of the data.
Example 2-1 In the introduction to this chapter, we described a case where Rob Whitner, owner of
Whitner Pontiac, is interested in collecting information on the selling prices of vehicles
sold at his dealership. What is the typical selling price? What is the highest selling
price? What is the lowest selling price? Around what value do the selling prices tend
to cluster? To answer these questions, we need to collect data. According to sales
records, Whitner Pontiac sold 80 vehicles last month. The price paid by the customer
for each vehicle is shown in Table 2-1. Summarize the selling prices of the vehicles sold
last month. Around what value do the selling prices tend to cluster?
i
Solution Table 2-1 contains quantitative data (recall from Chapter 1). These data are raw or
ungrouped data. With a little searching, we can find the lowest selling price ($19 320)
and the highest selling price ($50 719), but that is about all. It is difficult to get a feel
for the shape of the data by mere observation of the raw data. The raw data are more
easily interpreted if they are organized into a frequency distribution. The steps for
organizing data into a frequency distribution are outlined below.
1. Decide how many classes you wish to use. The goal is to use just enough groupings
or classes to reveal the shape of the distribution. Some judgment is needed here. Too
many classes or too few classes might not reveal the basic shape of the set of data.
In the vehicle selling price problem, for example, three classes would not give much
insight into the pattern of the data (see Table 2-2).
A useful recipe to determine the number of classes is the “2 to the k rule.” This
guide suggests you select the smallest number (k) for the number of classes such
that 2k (in words, 2 raised to the power of k) is greater than the number of data
points (n).
In the Whitner Pontiac example, there were 80 vehicles sold. So n 80. If we try
k 6, which means we would use 6 classes, then 26 64, somewhat less than 80.
Hence, 6 classes are not enough. If we let k 7, then 27 128, which is greater than
80. So the recommended number of classes is 7.
2. Determine the class width. Generally, the class width should be the same for all
classes. At the end of this section, we shall briefly discuss some situations where
unequal class widths may be necessary. All classes taken together must cover at
least the distance from the lowest value in the raw data up to the highest value.
Describing Data: Frequency Distributions and Graphic Presentation 35
TABLE 2-1: Selling Prices ($) at Whitner Pontiac Last Month
31 373 26 879 31 710 36 442 37 657 21 969 23 132
39 552 42 923 25 544 31 060 50 596 25 026 26 252
32 778 32 839 33 277 39 532 19 320 19 920 25 984
34 266 38 552 33 160 37 642 26 009 26 186 22 109
26 418 34 306 25 699 31 812 36 364 27 558 26492
31 978 35 085 36 438 45 086 27 169 29 231 32 420
35 110 19 702 23 505 50 719 22 175 23 050 26 728
28 400 28 831 25 149 30 518 25 819 27 154 27661
30 561 35 859 38 339 40 157 45 417 24 470 28 859
29 836 33 219 34 571 39 018 27 168 31 744 32 678
42 588 29 940 22 932 27 439 35 784 26 865 28 576
28 704 32 795 31103
TABLE 2-2: An Example of Too Few Classes
Vehicle Selling Price Number of Vehicles
19 000 up to 32 900 53
32 900 up to 46 800 25
46 800 up to 60 700 2
Total 80
36 Chapter Two
Expressing these words in a formula:
where H is the highest observed value, L is the lowest observed value, and k is the
number of classes.
In the Whitner Pontiac case, the lowest value is $19 320 and the highest value is
$50 719. If we wish to use 7 classes, the class width should be greater than ($50 719
$19 320)/7 $4485 571. In practice, this class width is usually rounded up to some
convenient number, such as a multiple of 10 or 100. We round this value up to $4490.
3. Set up the individual class limits. We should state class limits very clearly so that each
observation falls into only one class. For example, classes such as $19 000–$20 000
and $20 000–$21000 should be avoided because it is not clear whether $20 000 is in
the first or second class. In this text, we will use the format $19 000 up to $20 000 and
$20 000 up to $21 000 and so on. With this format it is clear that $19 999 goes into the
first class and $20 000 in the second.
Because we round the class width up to get a convenient class width, we cover a
larger than necessary range. For example, seven classes of width $4490 in the
Whitner Pontiac case result in a range of ($4490)(7) $31 430.
The actual range is $31 399, found by (H L 50 719 19 320). Comparing this
value to $31 430, we have an excess of $31. It is natural to put approximately equal
amounts of the excess in each of the two tails. As we have said before, we should also
select convenient multiples of 10 for the class limits. We shall use $19 310 as the
lower limit of the first class. The upper limit of the first class is then 23 800, found
by (19 310 4 490 23 800). Hence, our first class is from $19 310 upto $23 800. We
can determine the other classes (in dollars) similarly, (from $23 800 up to $28 290),
(from $28 290 up to $32 780), (from $32 780 up to $37 270), (from $37 270 up to
$41 760), (from $41 760 up to $46 250), and (from $46 250 up to $50 740).
4. Tally the selling prices into the classes. To begin, the selling price of the first vehicle
in Table 2-1 is $31 373. It is tallied in the $28 290 up to $32 780 class. The second
selling price in the first column is $39 552. It is tallied in the $37 270 up to
$41 760 class. The other selling prices are tallied in a similar manner. When all the
selling prices are tallied, we get Table 2-3(a).
Class width
H L
k
Statistics in
Action
Forestry and
the Canadian
Economy
Why is Canadian softwood
an important
commodity? To find
the answer, let us look
at some statistics
from the Statistics
Canada Web site
(www.statcan.ca).
• Logging and forestry
employed 68 000
workers, second only
to mining in primary
industries in the
year 2000
• Canada exported
$41 380.8 millions of
forestry products on
balance of payment
basis in the year
2000
• Quebec occupies
the most forestland
(839 000 km2)
• PEI covers the
least forestland
(3000 km2)
• Canada has
75 800 km2 of
forestland
All the numeric data
above are statistics,
and allow us to see
why logging and
forestry is important to
the Canadian economy.
• • •
TABLE 2-3: Construction of a Frequency Distribution
of Whitner Pontiac Data
(a) Tally Count
Classes ($) Tally
19 310 up to 23 800 |||| ||||
23 800 up to 28 290 |||| |||| |||| |||| |
28 290 up to 32 780 |||| |||| |||| ||||
32 780 up to 37 270 |||| |||| ||||
37 270 up to 41 760 |||| |||
41 760 up to 46 250 ||||
46 250 up to 50 740 ||
(b) Frequency Distribution
Selling Prices Frequency
($ thousands)
19.310 up to 23.800 10
23.800 up to 28.290 21
28.290 up to 32.780 20
32.780 up to 37.270 15
37.270 up to 41.760 8
41.760 up to 46.250 4
46.250 up to 50.740 2
Total 80
5. Count the number of items in each class. The number of observations in each class
is called the class frequency. In the $19 310 up to $23 800 class, there are 10 observations;
in the $23 800 up to $28 290 class there are 21 observations. Therefore, the
class frequency in the first class is 10 and the class frequency in the second class is
21. The sum of frequencies of all the classes equals the total number of observations
in the entire data set, which is 80.
Often it is useful to express the data in thousands, or some convenient units,
rather than the actual data. Table 2-3(b) reports the frequency distribution for
Whitner Pontiac’s vehicle selling prices where prices are given in thousands of
dollars rather than dollars.
Now that we have organized the data into a frequency distribution, we can summarize
the patterns in the selling prices of the vehicles for Rob Whitner. These observations
are listed below:
1. The selling prices ranged from about $19 310 to $50 740.
2. The largest concentration of selling prices is in the $23 800 up to $28 290 class.
3. The selling prices are concentrated between $23 800 and $37 270. A total of 56
(70 percent) of the vehicles are sold within this range.
4. Two of the vehicles sold for $46 250 or more, and 10 sold for less than $23 800.
By presenting this information to Rob Whitner, we give him a clearer picture of the
distribution of the selling prices for the last month.
We admit that arranging the information on the selling prices into a frequency distribution
does result in the loss of some detailed information. That is, by organizing the
data into a frequency distribution, we cannot pinpoint the exact selling price (such as
$23 820, or $32 800), and we cannot tell that the actual selling price of the least expensive
vehicle was $19 320 and of the most expensive vehicle was $50 719. However, the
lower limit of the first class and the upper limit of the largest class convey essentially
the same meaning. Whitner will make the same judgment if he knows the lowest price
is about $19 310 that he will make if he knows the exact selling price is $19 320. The
advantage of condensing the data into a more understandable form more than offsets
this disadvantage.
SELF- REVIEW 2-1
The commissions earned for the first quarter of last year by the 11 members of the
sales staff at Master Chemical Company are $1650, $1475, $1510, $1670, $1595,
$1760, $1540, $1495, $1590, $1625, and $1510.
(a) What are the values such as $1650 and $1475 called?
(b) Using $1400 up to $1500 as the first class, $1500 up to $1600 as the second
class, and so forth, organize data on commissions earned into a frequency
distribution.
(c) What are the numbers in the right column of your frequency distribution
called?
(d) Describe the distribution of commissions earned based on the frequency
distribution. What is the largest amount of commission earned? What is
the smallest?
Describing Data: Frequency Distributions and Graphic Presentation 37
38 Chapter Two
CLASS INTERVALS AND CLASS MIDPOINTS
We will use two other terms frequently: class midpoint and class interval. The midpoint,
also called the class mark, is halfway between the lower and upper class limits. It can
be computed by adding the lower class limit to the upper class limit and dividing by 2.
Referring to Table 2-3 for the first class, the lower class limit is $19 310 and the upper
limit is $23 800. The class midpoint is $21 555, found by ($19 310 $23 800)/2. The
midpoint of $21 555 best represents, or is typical of, the selling prices of the vehicles
in that class.
To determine the class interval, subtract the lower limit of the class from its upper
limit. The class interval of the vehicle selling price data is $4490, which we find by subtracting
the lower limit of the first class, $19 310, from its upper limit; that is, $23 800
$19 310 $4490. You can also determine the class interval by finding the distance
between consecutive midpoints. The midpoint of the first class is $21 555 and the midpoint
of the second class is $26 045. The difference is $4490.
A SOFTWARE EXAMPLE: FREQUENCY DISTRIBUTION
USING MEGASTAT
Chart 2-2 shows the frequency distribution of the Whitner Pontiac data produced by
MegaStat. The form of the output is somewhat different than the frequency distribution
in Table 2-3(b), but overall conclusions are the same.
Self-Review 2-2
The following table includes the grades of students who took Math 1021 during
Fall 2002.
40 55 50 55 28 60 25 55 60 65 70 64
62 70 50 65 55 48 69 25 64 58 55 71
(a) How many classes would you use?
(b) How wide would you make the classes?
(c) Create a frequency distribution table.
RELATIVE FREQUENCY DISTRIBUTION
It may be desirable to convert class frequencies to relative class frequencies to show
the fraction of the total number of observations in each class. In our vehicle sales
example, we may want to know what percentage of the vehicle prices are in the
$28 290 up to $32 780 class.
To convert a frequency distribution to a relative frequency distribution, each of the
class frequencies is divided by the total number of observations. Using the distribution
of vehicle sales again (Table 2-3(b), where the selling prices are reported in thousands of
dollars), the relative frequency for the $19 310 up to $23 800 class is 0.125, found by
dividing 10 by 80. That is, the price of 12.5 percent of the vehicles sold at Whitner
Pontiac is between $19 310 and $23 800. The relative frequencies for the remaining
classes are shown in Table 2-4.
EXCEL CHART 2-2: Frequency Distribution of Data in Table 2-1
MICROSOFT EXCEL INSTRUCTIONS
1. Click on MegaStat, Frequency Distributions,
Quantitative... .
2. In the Input Range field, enter the data
location.
3. Select Equal Width Interval, and input
interval size ( 4490 in our example).
4. Input value of lower boundary of
the first interval ( 19 310 in our example).
5. Deselect Histogram, and click OK.
Describing Data: Frequency Distributions and Graphic Presentation 39
TABLE 2-4: Relative Frequency Distribution of Selling Prices
at Whitner Pontiac Last Month
Selling Price ($ thousands) Frequency Relative Frequency Found by
19.310 up to 23.800 10 0.1250 «——— 10/80
23.800 up to 28.290 21 0.2625 «——— 21/80
28.290 up to 32.780 20 0.2500 «——— 20/80
32.780 up to 37.270 15 0.1875 «——— 15/80
37.270 up to 41.760 8 0.1000 «——— 8/80
41.760 up to 46.250 4 0.0500 «——— 4/80
46.250 up to 50.740 2 0.0250 «——— 2/80
Total 80 1.00100
1
Start
2
40 Chapter Two
SELF-REVIEW 2-3
Refer to Table 2-4, which shows the relative frequency distribution for the vehicles sold
last month at Whitner Pontiac.
(a) How many vehicles sold for $23 800 up to $28 290?
(b) What percentage of the vehicles sold for a price from $23 800 up to
$28 290?
(c) What percentage of the vehicles sold for $37 270 or more?
EXERCISES 2-1 TO 2-8
2-1. A set of data consists of 38 observations. How many classes would you recommend
for the frequency distribution?
2-2. A set of data consists of 45 observations. The lowest value is $0 and the highest
value is $29. What size would you recommend for the class interval?
2-3. A set of data consists of 230 observations. The lowest value is $235 and
the highest value is $567. What class interval would you recommend?
2-4. A set of data contains 53 observations. The lowest value is 42 and the highest is
129. The data are to be organized into a frequency distribution.
(a) How many classes would you suggest?
(b) What would you suggest as the lower limit of the first class?
2-5. The Wachesaw Outpatient Centre, designed for same-day minor surgery, opened
last month. Below are the numbers of patients served during the first 16 days.
27 27 23 24 25 28 35 33
34 24 30 30 24 33 23 23
(a) How many classes would you recommend?
(b) What class interval would you suggest?
(c) What lower limit would you recommend for the first class?
2-6. The Quick-Change Oil Company has a number of outlets in Hamilton, Ontario.
The numbers of oil changes at the Oak Street outlet in the past 20 days are
listed below. The data are to be organized into a frequency distribution.
65 98 55 62 79 59 51 90 72 56
70 62 66 80 94 79 63 73 71 85
(a) How many classes would you recommend?
(b) What class interval would you suggest?
(c) What lower limit would you recommend for the first class?
(d) Organize the number of oil changes into a frequency distribution.
(e) Comment on the shape of the frequency distribution. Also determine
the relative frequency distribution.
2-7. The local manager of Food Queen is interested in the number of times
a customer shops at her store during a two-week period. The responses of 51
customers were:
5 3 3 1 4 4 5 6 4 2 6 6 6 7 1
1 14 1 2 4 4 4 5 6 3 5 3 4 5 6
8 4 7 6 5 9 11 3 12 4 7 6 5 15 1
1 10 8 9 2 12
Describing Data: Frequency Distributions and Graphic Presentation 41
(a) Starting with 0 as the lower limit of the first class and using a class interval
of 3, organize the data into a frequency distribution.
(b) Describe the distribution. Where do the data tend to cluster?
(c) Convert the distribution to a relative frequency distribution.
2-8. Moore Travel, a nationwide travel agency, offers special rates on certain
Caribbean cruises to senior citizens. The president of Moore Travel wants additional
information on the ages of those people taking cruises. A random sample
of 40 customers taking a cruise last year revealed these ages:
77 18 63 84 38 54 50 59 54 56 36 26 50 34
44 41 58 58 53 51 62 43 52 53 63 62 62 65
61 52 60 60 45 66 83 71 63 58 61 71
(a) Organize the data into a frequency distribution, using 7 classes and 15
as the lower limit of the first class. What class interval did you select?
(b) Where do the data tend to cluster?
(c) Describe the distribution.
(d) Determine the relative frequency distribution.
FREQUENCY DISTRIBUTION WITH UNEQUAL CLASS INTERVALS
In constructing frequency distributions of quantitative data, generally, equal class
widths are assigned to all classes. This is because unequal class intervals present
problems in graphically portraying the distribution and in doing some of the computations,
as we will see in later chapters. Unequal class intervals, however, may be necessary
in certain situations to avoid a large number of empty, or almost empty, classes.
Such is the case in Table 2-5. Canada Customs and Revenue Agency (CCRA) used
unequal-sized class intervals to report the adjusted gross income on individual tax
returns. Had the CCRA used an equal-sized interval of, say, $1000, more than 1000
classes would have been required to describe all the incomes. A frequency distribution
with 1000 classes would be difficult to interpret. In this case, the distribution is easier
to understand in spite of the unequal classes. Note also that the number of income tax
returns or “frequencies” is reported in thousands in this particular table. This also
makes the information easier to digest.
TABLE 2-5: Adjusted Gross Income for Individuals Filing
Income Tax Returns
Adjusted Gross Income ($) Number of Returns (in thousands)
Under 2 000 135
2 000 up to 3 000 3 399
3 000 up to 5 000 8 175
5 000 up to 10 000 19 740
10 000 up to 15 000 15 539
15 000 up to 25 000 14 944
25 000 up to 50 000 4 451
50 000 up to 100 000 699
100 000 up to 500 000 162
500 000 up to 1 000 000 3
1 000 000 and over 1
42 Chapter Two
2.2 Stem-and-Leaf Displays
In Section 2.1, we showed how to organize quantitative data into a frequency distribution
so we could summarize the raw data into a meaningful form. The major advantage
of organizing the data into a frequency distribution is that we get a quick visual
picture of the shape of the distribution without doing any further calculation. That is,
we can see where the data are concentrated and also determine whether there are any
extremely large or small values. However, it has two disadvantages: (1) we lose the
exact identity of each value, and (2) we are not sure how the values within each class
are distributed. To explain, consider the following frequency distribution of the number
of 30-second radio advertising spots purchased by the 45 members of the Toronto
Automobile Dealers’ Association in 2001. We observe that 7 of the 45 dealers purchased
at least 90 but less than 100 spots. However, is the number of spots purchased
within this class clustered near 90, spread evenly throughout the class, or clustered
near 99? We cannot tell.
Number of Spots Purchased Frequency
80 up to 90 2
90 up to 100 7
100 up to 110 6
110 up to 120 9
120 up to 130 8
130 up to 140 7
140 up to 150 3
150 up to 160 3
Total 45
For a mid-sized data set, we can eliminate these shortcomings by using an alternative
graphic display called the stem-and-leaf display. To illustrate the construction of
a stem-and-leaf display using the advertising spots data, suppose the seven observations
in the 90 up to 100 class are 96, 94, 93, 94, 95, 96, and 97.
Let us sort these values to get: 93, 94, 94, 95, 96, 96, 97. The stem value is the leading
digit or digits, in this case 9. The leaves are the trailing digits. The stem is placed
to the left of a vertical line and the leaf values to the right. The values in the 90 up to
100 class would appear in the stem-and-leaf display as follows:
9 3 4 4 5 6 6 7
With the stem-and-leaf display, we can quickly observe that there were two dealers
who purchased 94 spots and that the number of spots purchased ranged from 93 to 97.
A stem-and-leaf display is similar to a frequency distribution with more information
(i.e., data values instead of tallies).
Stem-and-leaf display A statistical technique to present a set of data. Each
numerical value is divided into two parts. The leading digit(s) become(s) the
stem and the trailing digit(s) become(s) the leaf. The stems are located along
the vertical axis and the leaf values are stacked against one another along the
horizontal axis.
The following example will explain the details of developing a stem-and-leaf display.
i
Example 2-2 Table 2-6 lists the number of 30-second radio advertising spots purchased by each of
the 45 members of the Toronto Automobile Dealers’ Association last year. Organize the
data into a stem-and-leaf display. Around what values do the number of advertising
spots tend to cluster? What is the smallest number of spots purchased by a dealer and
the largest number purchased?
Solution From the data in Table 2-6 we note that the smallest number
of spots purchased is 88. So we will make the first stem value 8.
The largest number is 156, so we will have the stem values
begin at 8 and continue to 15. The first number in Table 2-6
is 96, which will have a stem value of 9 and leaf value of 6.
Moving across the top row, the second value is 93 and the
third is 88. After the first three data values are considered,
the display is shown opposite.
Organizing all the data, the stem-and-leaf display would appear as shown in
Chart 2-3(a).
The usual procedure is to sort the leaf values from smallest to largest. The last line,
the row referring to the values in the 150s, would appear as:
15 5 5 6
The final table would appear as shown in Chart 2-3(b), where we have sorted all of
the leaf values.
TABLE 2-6: Number of Advertising Spots Purchased during 2001
by Members of the Toronto Automobile Dealers’ Association
96 93 88 117 127 95 113 96 108 94
148 156 139 142 94 107 125 155 155 103
112 127 117 120 112 135 132 111 125 104
106 139 134 119 97 89 118 136 125 143
120 103 113 124 138
Describing Data: Frequency Distributions and Graphic Presentation 43
Stem Leaf
8 8
9 6 3
10
11
12
13
14
15
CHART 2-3: Stem-and-Leaf Display
a. b.
Stem Leaf
8 89
9 6 3 5 6 4 4 7
10 8 7 3 4 6 3
11 7 3 2 7 2 1 9 8 3
12 7 5 7 0 5 5 0 4
13 9 5 2 9 4 6 8
14 8 2 3
15 6 5 5
Stem Leaf
8 89
9 3 4 4 5 6 6 7
10 3 3 4 6 7 8
11 1 2 2 3 3 7 7 8 9
12 0 0 4 5 5 5 7 7
13 2 4 5 6 8 9 9
14 2 3 8
15 5 5 6
44 Chapter Two
You can draw several conclusions from the stem-and-leaf display. First, the lowest
number of spots purchased is 88 and the highest is 156. Two dealers purchased less
than 90 spots, and three purchased 150 or more. You can observe, for example, that
the three dealers who purchased more than 150 spots actually purchased 155, 155, and
156 spots. The concentration of the number of spots is between 110 and 139. There
were nine dealers who purchased between 110 and 119 spots and eight who purchased
between 120 and 129 spots. We can also tell that within the 120 up to 130 group, the
actual number of spots purchased was spread evenly throughout. That is, two dealers
purchased 120 spots, one dealer purchased 124 spots, three dealers purchased 125
spots, and two dealers purchased 127 spots.
We can also generate this information using Minitab. We have named the variable
Spots. The Minitab output is given on the next page.
The Minitab stem-and-leaf display provides some additional information regarding
cumulative totals. In Chart 2-4, the column to the left of the stem values has
numbers such as 2, 9, 15, and so on. The number 9 indicates that there are 9
observations of value less than the upper limit of the current class, which is 100. The
number 15 indicates that there are 15 observations less than 110. About halfway
down the column the number 9 appears in parentheses. The parentheses indicate that
the middle value appears in that row; hence, we call this row the median row. In this
case, we describe the middle value as the value that divides the total number of
observations into two equal parts. There are a total of 45 observations, so the middle
value, if the data were arranged from smallest to largest, would be the 23rd observation.
After the median row, the values begin to decline. These values represent the
“more than” cumulative totals. There are 21 observations of value greater than or
equal to the lower limit of this class, which is 120; 13 of 130 or more, and so on. Stemand-
leaf display is useful only for a mid-sized data set. When we use a stem-and-leaf
display for a large data set, we produce a large number of stems and/or leaves and are
not able to see the characteristics of a large data set.
In the stem-and-leaf display for Example 2-2, the leading digits (stems) take the
values from 8 to 15 and thus have 8 stems (8, 9, 10, 11, 12, 13, 14, 15) in units of 10.
However, in some data sets, stems assume only two or three values. Generating a stemand-
leaf display in these situations is not as easy as in Example 2-2. Let us look at
the sample of marks of 20 students in Math 2010:
50 52 54 53 65 60 45 43 57 62
56 58 51 61 46 44 69 55 64 59
The leading digits (units of 10) in this example assume only three values: 4, 5, and
6. Following the above procedure for drawing a stem-and-leaf display, the stem-and-leaf
display of the above data set looks like the one given below.
Stem Leaf
4 3 4 5 6
5 0 1 2 3 4 5 6 7 8 9
6 0 1 2 4 5 9
As we can see, this stem-and-leaf display has only three stems and does not display the
characteristics of the data set as well as if there were more stems. We can improve
the stem-and-leaf display by splitting each stem. For example, stem 4 can be split as
4 34
4 56
The first stem 4 contains leaves less than 5 and the second stem 4 contains leaves 5
and above.
The revised stem-and-leaf display is given below.
Other data sets may require even more splitting. The question of how much splitting
is necessary can be answered by the rule suggested by Tukey et al.1 For a sample
size 100, the number of stems should be the integer part of 2 n, where n is the sample
size; for n 100, the number of stems should be the integer part of 10 log10 n.
In our example of 20 students’ marks, the number suggested by the rule is 8. However,
we have 6 stems in our example, which is close to 8. Remember, the rule provides
a guideline for selecting the number of stems.
Describing Data: Frequency Distributions and Graphic Presentation 45
Stem Leaf
4 34
4 56
5 0 1 2 3 4
5 5 6 7 8 9
6 0 1 2 4
6 59
MINITAB CHART 2-4: Stem-and-Leaf Display of Data in Table 2-6
MINITAB INSTRUCTIONS
1. Click on Graph, and
Stem-and-leaf.
2. Enter the location of the
data in the variable field.
3. Enter the size of the
increment, ( 10 in our
example), in the increment
field.
4. Click OK.
1
2
3
46 Chapter Two
SELF-REVIEW 2-4
The price–earnings ratios for 21 stocks in the retail trade category are:
8.3 9.6 9.5 9.1 8.8 11.2 7.7 10.1 9.9 10.8 10.2
8.0 8.4 8.1 11.6 9.6 8.8 8.0 10.4 9.8 9.2
Organize this information into a stem-and-leaf display.
(a) How many values are less than 9.0?
(b) List the values in the 10.0 up to 11.0 category.
(c) What are the largest and the smallest price–earnings ratios?
EXERCISES 2-9 TO 2-14
2-9. The first row of a stem-and-leaf display appears as follows: 62 | 1 3 3 7 9.
Assume whole number values.
(a) What is the range of the values in this row?
(b) How many data values are in this row?
(c) List the actual values in this row.
2-10. The third row of a stem-and-leaf display appears as follows: 21 | 0 1 3 5 7 9.
Assume whole number values.
(a) What is the range of the values in this row?
(b) How many data values are in this row?
(c) List the actual values in this row.
2-11. The following stem-and-leaf display shows the number of units produced
per day in a factory.
1 3 8
1 4
2 5 6
9 6 0 1 3 3 5 5 9
(7) 7 0 2 3 6 7 7 8
9 8 5 9
7 9 0 0 1 5 6
2 10 3 6
(a) How many days were studied?
(b) How many observations are in the first class?
(c) What are the largest and the smallest values in the data set?
(d) List the actual values in the fourth row.
(e) List the actual values in the second row.
(f ) How many values are less than 70?
(g) How many values are 80 or more?
(h) How many values are between 60 and 89?
2-12. The following stem-and-leaf display reports the number of movies rented
per day at Video Connection.
3 12 6 8 9
6 13 1 2 3
10 14 6 8 8 9
13 15 5 8 9
15 16 3 5
20 17 2 4 5 6 8
23 18 2 6 8
(5) 19 1 3 4 5 6
22 20 0 3 4 6 7 9
16 21 2 2 3 9
12 22 7 8 9
9 23 0 0 1 7 9
4 24 8
3 25 1 3
1 26
1 27 0
(a) How many days were studied?
(b) How many observations are in the last class?
(c) What are the largest and the smallest values in the entire set of data?
(d) List the actual values in the fourth row.
(e) List the actual values in the next to the last row.
(f ) On how many days were fewer than 160 movies rented?
(g) On how many days were 220 or more movies rented?
(h) On how many days were between 170 and 210 movies rented?
2-13. A survey of the number of calls received by a sample of Southern Phone
Company subscribers last week revealed the following information. Develop
a stem-and-leaf display. How many calls did a typical subscriber receive?
What were the largest and the smallest number of calls received?
52 43 30 38 30 42 12 46 39 37 34 46 32
18 41 5
2-14. Aloha Banking Co. is studying the number of times a particular automated
teller machine (ATM) is used each day. The following is the number of times
it was used during each of the last 30 days. Develop a stem-and-leaf display.
Summarize the data on the number of times the machine was used: How many
times was the ATM used on a typical day? What were the largest and the smallest
number of times the ATM was used? Around what values did the number
of times the ATM was used, tend to cluster?
83 64 84 76 84 54 75 59 70 61 63 80 84
73 68 52 65 90 52 77 95 36 78 61 59 84
95 47 87 60
Describing Data: Frequency Distributions and Graphic Presentation 47
48 Chapter Two
2.3 Graphic Presentation
of a Frequency Distribution
Sales managers, stock analysts, hospital administrators, and other busy executives
often need a quick picture of the trends in sales, stock prices, or hospital costs. These
trends can often be depicted by the use of charts and graphs. The charts that depict
a frequency distribution graphically are the histogram, the stem-and-leaf display,
the frequency polygon, and the cumulative frequency polygon.
HISTOGRAM
One of the most common graphical methods of displaying frequency distribution of
a quantitative data is a histogram.
Histogram A graph in which classes are marked on the horizontal axis and
class frequencies on the vertical axis. The class frequencies are represented by
the heights of the rectangles, and the rectangles are drawn adjacent to each
other without any space between them.
Thus, a histogram describes a frequency distribution using a series of adjacent rectangles.
Since the height of each rectangle equals the frequency of the corresponding
class, and all the class widths are equal, the area of each rectangle is proportional to
the frequency of the corresponding class.
Example 2-3 Refer to the data in Table 2-7 on life expectancy of males at birth in 40 countries.
Construct a frequency distribution and a histogram. What conclusions can you reach
based on the information presented in the histogram?
Solution The data in Table 2-7 is a quantitative data. Therefore, the first step is to construct
a frequency distribution using the method discussed in Section 2.1 This is given in
Table 2-8. (In Table 2-8, we also give relative frequencies. These will be discussed later.)
i
TABLE 2-7: Life Expectancy of Males at Birth
Country Life Expectancy
(years)
Afghanistan 45
Albania 69.9
Angola 44.9
Argentina 69.6
Armenia 67.2
Australia 75.5
Austria 73.7
Bahamas 70.5
Bahrain 71.1
Bangladesh 58.1
Barbados 73.7
Belarus 62.2
Belgium 73.8
Bermuda 71.7
Source: Life Expectancy at Birth (Males), United Nations Statistics Divisions, 1996–2000
Country Life Expectancy
(years)
Bhutan 59.5
Botswana 46.2
Brazil 63.1
Bulgaria 67.6
Cambodia 51.5
Canada 76.1
Chad 45.7
Chile 72.3
China 67.9
Congo 48.3
Cuba 74.2
Czech
Republic 70.3
Denmark 73
Country Life Expectancy
(years)
Egypt 64.7
France 74.2
Germany 73.9
Hungary 66.8
India 62.3
Iran 68.5
Japan 76.8
Kenya 51.1
Nepal 57.6
UK 74.5
USA 73.4
Venezuela 70
Zambia 39.5
To construct a histogram, class frequencies are scaled along the vertical axis
(y-axis) and either the class limits or the class midpoints are scaled along the horizontal
axis (x-axis).
From the frequency distribution, the frequency of the class 36 up to 43 is 1.
Therefore, the height of the column for this class is 1. Make a rectangle whose width
spreads from 36 to 43 with the height of one unit. Repeat the process for the remaining
classes. The completed histogram should resemble the graph presented in Chart
2-5. The double slant on the x-axis indicates that the class limits did not start at zero.
That is, the division between 0 and 36 is not linear. In other words, the distance
between 0 and 36 is not the same as the distance between 36 and 43, between 43 and
50, and so on.
From Chart 2-5, we conclude that:
• the lowest life expectancy is about 36 years and the highest is about 78 years.
• the class with the highest frequency (15) is 71 up to 78. That is, 15 countries have
a life expectancy from 71 up to 78 years.
• the class with the lowest frequency (1) is 36 up to 43 years. That is, there is only one
country with a life expectancy from 36 up to 43.
• the histogram is j-shaped. There is a tail on the left side of the class with the highest
frequency (mode), and no tail on its right side.
TABLE 2-8: Frequency and Relative Frequency Distribution
of Life Expectancy Data
Life Expectancy Frequency Relative Frequency Found by
36 up to 43 1 0.025 1/40
43 up to 50 5 0.125 5/40
50 up to 57 2 0.050 2/40
57 up to 64 6 0.150 6/40
64 up to 71 11 0.275 11/40
71 up to 78 15 0.375 15/40
Total 40 1.000
16
14
12
10
8
6
4
2
Frequency
36 43 50 57 64 71 78
Histogram of Life
Expectancy at Birth (Males)
CHART 2-5: Histogram of Life Expectancy for Males at Birth
Describing Data: Frequency Distributions and Graphic Presentation 49
50 Chapter Two
COMMON DISTRIBUTION SHAPES
According to the shapes of histograms, distributions can be classified into (i) symmetrical
and (ii) skewed.
A symmetrical distribution is one in which, if we divide its histogram into two
pieces by drawing a vertical line through its centre, the two halves formed are mirror
images of each other. This is displayed in Chart 2-6(a).
A distribution that is not symmetrical is said to be skewed.
For a skewed distribution, it is quite common to have one tail of the distribution
longer than the other. If the longer tail is stretched to the right, the distribution is said to
be skewed to the right. If the longer tail is stretched to the left, it is said to be skewed
to the left. These are displayed in Charts 2-6(b) and (c) below.
For a symmetrical distribution, the centre, or the typical value, of the distribution
is well defined. For a skewed distribution, however, it is not that easy to define the centre.
We shall discuss this in detail in the next chapter.
Another commonly used classification of distributions is according to its number
of peaks. When the histogram has a single peak, the distribution is called unimodal.
A bimodal distribution is one in which the histogram has two peaks not necessarily
equal in height.
RELATIVE FREQUENCY HISTOGRAM
A relative frequency histogram is a graph in which classes are marked on the horizontal
axis and the relative frequencies (frequency of a class/total frequency) on the vertical axis.
Let us refer again to the data in Table 2-7 on life expectancy of males at birth in 40
countries. In Table 2-8 we also give a relative frequency distribution corresponding to this
data. For example, the relative frequency of the class 43 up to 50 is 0.125 (5/40).
We follow the procedure used in drawing a histogram to draw a relative frequency histogram.
Chart 2-7 shows the relative frequency histogram of the life expectancy data.
A relative frequency histogram has the following important properties:
• The shape of a relative frequency histogram of a data set is identical to the shape of
its histogram. (Verify this for the life expectancy data.)
Symmetrical
(a)
Skewed Right
(b)
Skewed Left
(c)
CHART 2-6: Common Distribution Shapes
• It is useful in comparing shapes of two or more data sets with different total
frequencies. (Note that when total frequencies of two data sets are different, histograms
of these data sets cannot be compared. For example, total frequency of one
data set may be 1000, while that of the other data set may be 100. But relative frequencies
of any data set add up to 1.0.)
• The area of the rectangle corresponding to a class interval equals (relative frequency
of the class) (class width). For example, the relative frequency of class 43 up to 50
is 0.125 (12.5 percent of the countries listed in Table 2-7 have life expectancy in this
class). The area of the corresponding rectangle is (0.125)(50 43) 0.875.
The total area under the entire relative frequency histogram is therefore (class
width) (sum of relative frequencies of all the classes) class width. (This is because
the sum of the relative frequency of all classes equals 1.)
If we scale the height of each rectangle by 1/(class width), then the total area under
each rectangle of the scaled relative frequency histogram will be equal to its relative
frequency, and the total area under the entire scaled relative frequency histogram will
be equal to 1.
A histogram provides an easily interpreted visual representation of the frequency
distribution of a given raw data. The shape of the histogram is the same whether we
use the actual frequency distribution or the relative frequency distribution. We shall
see in later chapters the importance of shapes in determining the appropriate method
of statistical analysis.
HISTOGRAM USING EXCEL AND MINITAB
We can plot a histogram using MegaStat by following the same instructions as those
for the construction of a frequency distribution, except that in this case, we do not
deselect “histogram.” We give below instructions for plotting a histogram using Excel
(without Megastat) and Minitab.
Relative Frequency
Life Expectancy
0.40
0.30
0.25
0.20
0.15
0.10
0.05
36 43 50 57 64 71 78
CHART 2-7: Relative Frequency Histogram of Life Expectancy
at Birth (Males)
Describing Data: Frequency Distributions and Graphic Presentation 51
52 Chapter Two
MICROSOFT EXCEL
INSTRUCTIONS
1. Enter the data in the first
column of the worksheet.
2. In the next column, enter a label and call it Bin. In
this column,
enter the upper limit of each class.
3. Click on Tools, Data Analysis, Histogram, and OK.
4. Enter the location of data in the Input Range.
5. Enter the location of Bin Range.
6. Check Label box, chart output, and click OK.
7. Click on any rectangle in the chart
and then right click the mouse.
8. Click Format Data Series, Select Options,
reduce gap width to zero, and click OK.
1
Start
3
EXCEL CHART 2-8: Histogram of Life Expectancy
2
MINITAB CHART 2-9: Histogram of Life Expectancy
MINITAB INSTRUCTIONS
1. Click on Graph, and Histogram.
2. Type the variable name in box 1 of
Graph variable.
3. Select bar under Display and Graph under
For each.
4. Click Options.
5. Either click the radio button Number of
Intervals and enter the number of intervals (6
in our example), or click the radio button cutpoint,
Select Midpoint/Cutpoint positions and
enter limits of all the classes in the
midpoint/cutpoint positions box:
(in our example 36 43 50 57 64 71 78).
6. Click OK and again Click OK.
1
2
3
4
Describing Data: Frequency Distributions and Graphic Presentation 53
54 Chapter Two
17.065 26.045 35.025 44.005 52.985 57.475
0.04
0.08
0.12
0.16
0.20
0.24
0.28
0.32
Relative frequency
Selling price ($000s)
Whitner
MidTown
FREQUENCY POLYGON
The construction of a frequency polygon is similar to the construction of a histogram.
It consists of line segments connecting the points formed by the intersections
of the class midpoints and the class frequencies. The construction of frequency
polygon is illustrated in Chart 2-10. We use the vehicle prices for the cars sold last
month at Whitner Pontiac. The midpoint of each class is scaled on the x-axis and the
class frequencies on the y-axis. Recall that the class midpoint is the value at the centre
of a class and represents the values in that class. The class frequency is the
number of observations in a particular class. The vehicle selling prices at Whitner
Pontiac are:
Selling Price ($ thousands) Midpoint Frequency
19.310 up to 23.800 21.555 10
23.800 up to 28.290 26.045 21
28.290 up to 32.780 30.34 20
32.780 up to 37.270 35.23 15
37.270 up to 41.760 39.12 8
41.760 up to 46.250 44.005 4
46.250 up to 50.740 48.495 2
Total 80
As noted earlier, the 19.310 up to 23.800 class is represented by the midpoint 21.555.
To construct a frequency polygon, we move horizontally on the graph to the midpoint
21.555 and then vertically to 10, the class frequency, and place a dot. The x and y values
of this point are called the coordinates. The coordinates of the next point are x 26.045
and y 21. The process is continued for all classes. Then the points are connected in
order. That is, the point representing the lowest class is joined to the one representing
the second class, and so on. Note in Chart 2-10 that to complete the frequency polygon,
two additional points with x co-ordinates 17.065 and 52.985 and with 0 frequencies (that
is, points on the x-axis), are added to anchor the polygon. These two values are derived
by subtracting the class width of 4.49 from the lowest midpoint (21.555) and adding 4.49
to the highest midpoint (48.495) in the frequency distribution.
CHART 2-10: Frequency Polygon
of the Selling Prices of 80
Vehicles at Whitner Pontiac
0 10 20 30 40 50 60
5
10
15
20
25
Selling price ($000s)
Frequency
CHART 2-11: Distribution of Selling Prices
at Whitner Pontiac and
Midtown Cadillac
Both the histogram and the frequency polygon allow us to get a quick picture of
the main characteristics of the data (highs, lows, points of concentration, etc.).
Although the two representations are similar in purpose, the histogram has the advantage
of depicting each class as a rectangle, with the height of the rectangular bar
representing the number of frequencies in each class. The frequency polygon, in turn,
has an advantage over the histogram. It allows us to directly compare two or more
frequency distributions. Suppose Rob, the owner of Whitner Pontiac, wants to compare
the sales last month at his dealership with those at Midtown Cadillac. To do this,
two frequency polygons are constructed, one on top of the other, as shown in Chart
2-11. It is clear from the chart that the total sales volume at each dealership is more
or less the same.
SELF-REVIEW 2-5
The annual imports of a selected group of electronic suppliers are shown in the
following frequency distribution.
Imports ($ millions) Number of Suppliers
2 up to 5 6
5 up to 8 13
8 up to 11 20
11 up to 14 10
14 up to 17 1
(a) Draw a histogram.
(b) Draw a frequency polygon.
(c) Summarize the important features of the distribution (such as low and
high values, concentration, etc.).
EXERCISES 2-15 TO 2-18
2-15. Molly’s Candle Shop has several retail stores in Vancouver. Many of Molly’s
customers ask her to ship their purchases. The following chart shows
the number of packages shipped per day for the last 100 days.
(a) What is this chart called?
(b) What is the total number of frequencies?
(c) What is the class interval?
(d) What is the class frequency for the 10 up to 15 class?
0 5 10 15 20 25 30 35
10
20
30
Frequency
Number of packages
5
13
28
23
18
10
3
Describing Data: Frequency Distributions and Graphic Presentation 55
56 Chapter Two
(e) What is the relative frequency for the 10 up to 15 class?
(f ) What is the midpoint for the 10 up to 15 class?
(g) On how many days were there 25 or more packages shipped?
2-16. The following chart shows the number of patients admitted daily to Memorial
Hospital through the emergency room.
(a) What is the midpoint of the 2 up to 4 class?
(b) On how many days were 2 up to 4 patients admitted?
(c) Approximately how many days were studied?
(d) What is the class interval?
(e) What is this chart called?
2-17. The following frequency distribution represents the number of days during
a year that employees at J. Morgan Manufacturing Company were absent from
work due to illness.
Number of Days Absent Number of Employees
0 up to 3 5
3 up to 6 12
6 up to 9 23
9 up to 12 8
12 up to 15 2
Total 50
(a) Construct a relative frequency histogram.
(b) What proportion of the total area under the relative frequency histogram
is contained above the interval 3 up to 12?
2-18. A large retailer is studying the lead time (elapsed time between when an order
is placed and when it is filled) for a sample of recent orders. The lead times are
reported in days.
Lead Time (days) Frequency
0 up to 5 6
5 up to 10 7
10 up to 15 12
15 up to 20 8
20 up to 25 7
Total 40
(a) How many orders were studied?
(b) What is the midpoint of the first class?
(c) What are the coordinates of the point on the frequency polygon
corresponding to the first class?
0 2 4 6 8 10 12
Number of patients
10
20
30
Frequency
(d) Draw a histogram.
(e) Draw a frequency polygon.
(f ) Interpret the lead times using the two charts.
CUMULATIVE FREQUENCY DISTRIBUTIONS
Let us consider again the distribution of the selling prices of vehicles at Whitner
Pontiac. Suppose we were interested in the number of vehicles that sold for less than
$28 290. These numbers can be approximated by developing a cumulative frequency
distribution and portraying it graphically in a cumulative frequency polygon, which is
also called an ogive.
Example 2-4 Refer to Table 2-4 on page 39. Construct a less than cumulative frequency polygon.
Fifty percent of the vehicles were sold for less than what amount? Twenty-five of the
vehicles were sold for less than what amount?
Solution As the name implies, a cumulative frequency distribution and a cumulative frequency
polygon require cumulative frequencies. The cumulative frequency of a class is the number
of observations fewer than the upper limit of that class. For example, in Table 2-10,
the frequency distribution of the vehicle selling prices at Whitner Pontiac is repeated
from Table 2-4. The cumulative frequency of the class 23.800 up to 28.290 is 31. How
did we get it? We added the number of vehicles sold for less than $23 800 (which equals
10) to the 21 vehicles sold in the next higher class. Thus the number of vehicles sold
for less than $28 290 is 31. Similarly, the cumulative frequency of the next higher class
is 10 21 20 51. The process is continued for all the classes.
To plot a cumulative frequency distribution, scale the upper limit of each class
along the x-axis and the corresponding cumulative frequencies along the y-axis. We
label the vertical axis on the left in units and the vertical axis on the right in percent.
In the Whitner Pontiac example, the vertical axis on the left is labelled from 0 to 80
(vehicles sold) and on the right from 0 to 100 percent. The value of 50 percent corresponds
to 40 vehicles sold.
To begin the plotting, 10 vehicles sold for less than $23 800, so the first point in the
plot is at x 23.80 and y 10. The coordinates of the next point are x 28.29 and
y 31. The rest of the points are plotted and then the dots are connected to form
Chart 2-12. Close the lower end of the graph by extending the line to the lower limit
of the first class. To find the selling price below which half the cars sold, we draw a line
from the 50-percent mark on the right-hand vertical axis over to the polygon, then
drop down to the x-axis and read the selling price. The value of the x-axis is about
TABLE 2-10: Cumulative Frequency Distribution for Selling Prices
at Whitner Pontiac Last Month
Selling Price ($ thousands) Frequency Cumulative Frequency Found by
19.310 up to 23.800 10 10 «—— (10 0)
23.800 up to 28.290 21 31 «—— (10 21)
28.290 up to 32.780 20 51 «—— (10 21 20)
32.780 up to 37.270 15 66
37.270 up to 41.760 8 74
41.760 up to 46.250 4 78
46.250 up to 50.740 2 80
Total 80
Describing Data: Frequency Distributions and Graphic Presentation 57
58 Chapter Two
$29 000. To find the price below which 25 of
the vehicles sold, we locate the value of 25 on
the left-hand vertical axis. Next, we draw
a horizontal line from the value of 25 to the
polygon, and then drop down to the x-axis and
read the price; it is about 26. So, we estimate
that 25 of the vehicles sold for less than
$26 000. We can also estimate the percentage
of vehicles sold for less than $39 000. We begin
by locating the value of 39 on the x-axis,
then moving vertically to the polygon and then
horizontally to the vertical axis on the right.
The value is about 87.5 percent. We therefore
conclude that 87.5 percent of the vehicles sold
for less than $39 000.
SELF-REVIEW 2-6
The following table provides information on the annual net profits of 34 small companies.
Annual Net Profits ($ thousands) Number of Companies
65 up to 75 1
75 up to 85 6
85 up to 95 7
95 up to 105 12
105 up to 115 5
115 up to 125 3
(a) What is the table called?
(b) Develop a cumulative frequency distribution and draw a cumulative
frequency polygon for the distribution.
(c) Based on the cumulative frequency polygon, find the number of companies
with annual net profits of less than $105 000.
EXERCISES 2-19 TO 2-22
2-19. The following table lists the salary distribution of full-time instructors in
a community college.
Salary ($) Number of Instructors
28 000 up to 33 000 5
33 000 up to 38 000 6
38 800 up to 43 000 4
43 000 up to 48 000 3
48 000 up to 53 000 7
Selling price ($000s)
Percent of vehicles sold
Number of vehicles sold
10 20 30 40 50
10
30
50
70
80
25
50
75
100
CHART 2-12: Cumulative
Frequency
Distribution
for Vehicle
Selling Price
(a) Develop a cumulative frequency distribution.
(b) Develop a cumulative relative frequency distribution.
(c) How many instructors earn less than $33 000?
(d) Seventy-two percent of instructors earn less than what amount?
2-20. Active Gas Services mailed statements of payments due to 70 customers.
The following amounts are due:
Amount ($) Number of Customers
70 up to 80 5
80 up to 90 20
90 up to 100 10
100 up to 110 11
110 up to 120 14
120 up to 130 10
(a) Draw a cumulative frequency polygon.
(b) What number of customers owes less than $100?
2-21. Refer to the frequency distribution of the annual number of days
the employees at the J. Morgan Manufacturing Company were absent from
work due to illness, given in Exercise 2-17.
(a) How many employees were absent less than three days annually?
How many were absent less than six days due to illness?
(b) Convert the frequency distribution to a less than cumulative frequency
distribution.
(c) Portray the cumulative distribution in the form of a less than cumulative
frequency polygon.
(d) From the cumulative frequency polygon, calculate the number of days
during which, about three out of four employees were absent, due to
illness?
2-22. Refer to the frequency distribution of the lead time to fill an order given in
Exercise 2-18.
(a) How many orders were filled in less than 10 days? In less than 15 days?
(b) Convert the frequency distribution to a less than cumulative frequency
distribution.
(c) Develop a less than cumulative frequency polygon.
(d) About 60 percent of the orders were filled in fewer than how many days?
2.4 Graphical Methods for Describing
Qualitative Data
The histogram, the stem-and-leaf display, the frequency polygon, and the cumulative
frequency polygon all are used to display a frequency distribution of quantitative data
and all have visual appeal. In this section, we will examine the simple bar chart, the
clustered bar chart, the stacked bar chart, the pie chart, and the line chart for
depicting frequency distribution of qualitative data.
Describing Data: Frequency Distributions and Graphic Presentation 59
60 Chapter Two
SIMPLE BAR CHART
A bar chart can be used to depict any level of measurement: nominal, ordinal, interval,
or ratio. (Recall our discussion of the levels of measurement of data in Chapter 1.)
Let us look at the following example.
Example 2-5 The following table shows the number of students enrolled in each of the five business
programs in a certain community college in the year 2000.
Program Students
Accounting 200
Industrial Relations 150
Financial Planning 250
Marketing 290
Management Studies 275
Represent this data using a bar chart.
Solution The qualitative variable contains five categories: Accounting, Industrial Relations,
Financial Planning, Marketing, and Management Studies. The frequency (number of
students) for each category is given. As the variable is qualitative, we select a bar chart
to depict the data. To draw the bar chart, we place categories on the horizontal axis at
regular intervals. We mark the frequency of each category on the vertical axis. Above
each category, we draw a rectangle whose height corresponds to the frequency of the
category. With this chart, it is easy to see that the highest enrollment is in Marketing
and the lowest is in the Industrial Relations program. This chart is vertical, but a horizontal
bar chart can also be drawn by hand or using software such as Excel or Minitab.
Horizontal bars are preferred for large category labels.
Chart 2-13 is produced using the data from Example 2-5 in Excel.
CLUSTERED BAR CHART
A clustered bar chart is used to summarize two or more sets of data. Consider
Example 2-6.
Example 2-6 The following table shows the number of students enrolled in five business programs
in a community college in 2000 and 2001.
Program Students (2000) Students (2001)
Accounting 200 300
Industrial Relations 150 200
Financial Planning 250 230
Marketing 290 230
Management Studies 275 304
Construct a clustered bar chart for this data.
EXCEL CHART 2-13: Bar Chart for Enrollment in Different Programs
1. Click Chart Wizard.
2. Select Chart Type column and click Next.
3. Enter the location of data (in our case, data
on names of five categories and enrollment
figures) in the Data Range field.
5. Click Series and enter students in the name
field.
6. Click Next.
7. In Chart Title, type Bar Graph: Students’
enrollment.
8. In Category (X) axis box, type Program,
and in Value (Y) axis box, type Students.
9. Click Finish.
1
Start
2
Describing Data: Frequency Distributions and Graphic Presentation 61
62 Chapter Two
Solution As there are two sets of data (data series) for each category, we can summarize both
sets of data simultaneously using a clustered bar chart. Steps to draw a clustered bar
chart are the same as for the bar chart, except that for each category we draw two
rectangles: one for 2000 and the other for 2001. The height of the Accounting rectangle
for 2000 shows the frequency in that program for 2000 and the height of the
Accounting rectangle for 2001 shows the frequency in that program for 2001. Both rectangles
are side by side without any space between them. We repeat the process for
each category.
We use Excel again to draw a clustered bar chart (see Chart 2-14). The instructions
are almost the same as those in the case of a simple bar chart. The only difference
is that, we enter the location of the entire data (data on names of categories and
enrollment figures for 2000 and 2001) in the data range field. Then when we click on
Series, we give a name to each of the series (in our case, we give names year 2000 and
year 2001). The computer output shows enrollment in 2000 and 2001 in one frame.
The frequencies (number of students) in 2000 and 2001 for each program are shown
side by side with no space between bars. We can see that enrollment in three programs
(Accounting, Industrial Relations, and Management Studies) increased in 2001, while
enrollment in Marketing and Financial Planning has decreased in 2001.
STACKED BAR CHART
In a stacked bar chart, the values in different data sets corresponding to the same
category are stacked in a single bar. For example, an Excel output for stacked bar
chart for data in Example 2-6 is shown in Chart 2-15.
EXCEL CHART 2-14: Clustered Bar Chart of Enrollment in 2000 and 2001
1
Start
The total height of the Accounting bar is 500, which equals total number of students
in Accounting for the years 2000 and 2001 combined. This is divided into two
parts: the bottom part (of height 200) shows enrollment during the year 2000, and the
top part (of height 300) shows enrollment during 2001. We can compare the enrollments
in 2000 and 2001 for each program. We can also compare the enrollments in different
programs for 2000 because the baselines of bars representing programs are all
anchored to the horizontal axis. For example, the enrollment in 2000 is highest in the
Marketing program and lowest in the Industrial Relations program. Due to the floating
baselines of bars for 2001, we are not able to visualize the difference in the enrollments
for programs in 2001.
In a variation of the stacked bar chart called a 100-percent stacked bar chart,
the corresponding data sets for each category are stacked as a percentage of the total.
For example, in the data from Example 2-6, the percentage enrollment in Accounting
for 2000 is 40 percent (200/500)(100) of the total enrollment in Accounting. The percentage
enrollment for Accounting in 2001 is 60 percent.
To produce a 100-percent stacked bar chart, the menu sequence is the same except
that we select Chart Subtype 100-percent stacked column.
PIE CHART
A pie chart, like a bar chart, is also used to summarize qualitative data. It is used to
display the percentage of relative frequency of each category by partitioning a circle
into sectors. The size of a sector is proportional to the percentage of relative frequency
of the corresponding category.
MICROSOFT EXCEL
INSTRUCTIONS
1. Click Chart Wizard, then
select chart subtype Stacked
Column, and click Next.
2. Enter the data location in
the Data Range field.
3. Click Series and type 2000
in the Name field; click
Series 2 and type 2001 in
the name field.
4. Click Next.
5. In the Chart Title field, type
stacked bar chart of enrollment
in 2000 and 2001.
6. Type programs in Category
(x) field, and enrollment in
the Value (y) field. Click on
Data Label and then click
the Show Value radio button.
7. Click Finish.
Start
Describing Data: Frequency Distributions and Graphic Presentation 63
EXCEL CHART 2-15: Stacked Bar Chart Enrollments in 2000 and 2001
64 Chapter Two
EXCEL CHART 2-16: Pie Chart of the Enrollment in Programs
MICROSOFT EXCEL INSTRUCTIONS
1. Click Chart Wizard, select Pie, and click Next.
2. Enter the location of data (categories and their
frequencies) in the Data Range field.
3. Click Next, Title and enter student enrollment in
the Chart Title field.
4. Click Data Label and the radio button Show Value.
5. Click Next, the radio button As a New Sheet, and then click Finish.
Pie Chart of Enrollment in Programs
Accounting
Industrial Relations
Financial Planning
Marketing
Management Studies
17%
13%
25% 21%
24%
Start
1
Example 2-7 Draw a pie chart for the data in Example 2-5 (see page 60).
Solution To draw a pie chart, we first calculate the percentage of relative frequency for each
category.
Program Percentage Relative Frequency
Accounting (200/1 165)(100) 17.1
Industrial Relations (150/1 165)(100) 12.9
Financial Planning (250/1 165)(100) 21.5
Marketing (290/1 165)(100) 24.9
Management Studies (275/1 165)(100) 23.6
An entire circle corresponds to 360 degrees; therefore, a one-percent relative frequency
observation corresponds to 3.6 degrees (360/100). Therefore, the sector angle
for the Accounting program is (3.60)(17.1) 61.6 degrees. Using a protractor, we
mark 0 degrees, 90 degrees, 270 degrees, and 360 degrees on a circle. To plot 17.1
percent for Accounting, we draw a line from the centre of the circle to 0 degrees on
the circle and then from the centre of the circle to 61.6 degrees on the circle. The area
of this “slice” represents 17.1 percent of total students enrolled in the Accounting
program. Next we add 17.1 percent of students enrolled in the Accounting program to
12.9 percent of students enrolled in the Industrial Relations program; the result is
30.0 percent. The angle corresponding to 30.0 percent is (3.60)(3.00) 108 degrees.
We draw a line from the centre of the circle to 108 degrees. Now the sector formed by
joining the line from the centre of the circle to 61.8 degrees and from the centre of
the circle to 108.2 degrees on the circle represents 12.9 percent of students enrolled
in the Industrial Relations program. We continue the process for the other programs.
Because the areas of the sectors, or “slices,” represent the relative frequencies of
the categories, we can quickly compare them.
We can use Excel and Minitab to draw a pie chart. The instructions for this are
given in Charts 2-16 and 2-17.
MINITAB CHART 2-17: Pie Chart of the Enrollment in Programs
MINITAB INSTRUCTIONS
1. Click on Graph, Pie Chart, and
Chart Table.
2. Click Categories in and type in
the column containing the
categories.
3. Click Frequencies in and type in
the cell number for the frequencies.
4. Click Title Box and type the title
(in our example, we give title.
Enrollment in Different Programs).
5. Click OK.
2
1
Describing Data: Frequency Distributions and Graphic Presentation 65
10
DJIA
10,735.57
4:31 PM EST
The world’s coolest investment charting and research site.
IndexWatch major market indexes Refresh Launch
WWW.BigCharts.com
@BigCharts.com
11 12 1 2 3
10,850
2 79.73
2 0.74%
10,800
10,750
10,700
10 11 12 1 2 3
3,900
3,850
3,800
3,750
3,700
NASDAQ
3,756.39
4:48 PM EST @BigCharts.com
2 65.37
2 1.71%
CHART 2-18: Market Summary on June 6, 2000
66 Chapter Two
It may be noted that in Excel, percentage values are rounded off to the nearest
whole number. In Minitab, the percentage values are rounded off to one decimal place.
From the pie charts, we see that the highest enrollment is in the Marketing program
and the lowest is in the Industrial Relations program. In addition, we also observe that
the enrollment in Marketing is almost twice the enrollment in the Industrial Relations
program. (The sector corresponding to Marketing is almost twice as big.)
A pie chart is meaningful when we do not use more than six or seven different data
values. If we do, we lose clarity and cannot interpret the pie chart correctly. The other
limitation of the pie chart is that we can use it for only one data series.
SELF- REVIEW 2-7
The total consumer credit (excluding mortgages) for the year 2000 is given below.
Financial Institution Consumer Credit
($ millions)
Chartered Banks 119 837
Trust and Mortgage 1 959
Credit Unions 15 345
Life Insurance Companies 4 443
Finance Companies 12 734
Special-Purpose Corporations 29 008
(a) Draw a pie chart. (b) Interpret the pie chart.
LINE CHART
A line chart is often used to depict changes in the value of a variable over a period. Time values
are labelled chronologically across the horizontal axis and values of the variable along
the vertical axis. A line is drawn through data points. This line chart is also nown as a timeseries
chart. It is widely used in newspapers and magazines to show the variation of data
over a given period, for example to depict the changing values over different periods of the
Dow Jones Industrial Average, the Toronto Stock Exchange S&P/TSX composite index, and
the NASDAQ. The line chart is also used to display two or more data series simultaneously
for a given period, for example share price and price–earning ratios, (the return on shares
of a company), versus the S&P/TSX. Chart 2-18 shows the Dow Jones Industrial Average
and the NASDAQ, the two most reported measures of business activity, on June 6, 2000.
2.5 Misleading Graphs
When you purchase a computer for your home or office, it usually includes some
graphics and spreadsheet software, such as Excel. This software will produce effective
charts and graphs; however, you must be careful not to mislead readers or misrepresent
the data. In this section we present several examples of charts and graphs
that are misleading. Whenever you see a chart or graph, study it carefully. Ask yourself
what the writer is trying to show you. Could the writer have any bias?
One of the easiest ways to mislead the reader is to make the range of the y-axis
very small in terms of the units. A second method is to begin at some value other than
0 on the y-axis. In Chart 2-19(a), it appears there has been a dramatic increase in
sales from 1989 to 2000. However, during that period, sales increased only 2 percent
(from $5.0 million to $5.1 million)! In addition, observe that the y-axis does not begin
at 0.
The vertical axis does not have to start at zero. It can start at some value other
than zero. If we cannot detect the variation in data with zero as the starting point on the
vertical axis, we should consider some value other than zero so that we can see
the variation.2
Chart 2-19(b) gives the correct impression of the trend in sales. Sales are almost
flat from 1989 to 2000; that is, there has been practically no change in sales during
the 10-year period.
Without much comment, we ask you to look at each of the following scenarios and
carefully decide whether the intended message is accurate.
(a)
1989 90 91 92 93 94 95 96 97 98 99 2000
0
1
2
3
4 5
6
7 8
9
10
Sales ($ millions)
Year
(b)
CHART 2-19: Sales of Matsui Nine-Passenger Vans, 1989–2000
Describing Data: Frequency Distributions and Graphic Presentation 67
68 Chapter Two
Scenario 1
The following chart was adapted from an advertisement for the new Wilson Ultra
Distance golf ball. The chart shows that the new ball gets the longest distance, but what
is the scale for the horizontal axis? How was the test conducted?
Maybe everybody
can’t hit a ball like
John Daly. But
everybody wants
to. That’s why Wilson © is
introducing the new Ultra ©
Distance ball. Ultra Distance
is the longest, most accurate
ball you’ll ever hit.
Wilson has totally redesigned this ball from the inside out, making Ultra
Distance a major advancement in golf technology.
Scenario 2
Fibre Glass Inc., based in Red Deer, Alberta, makes and installs Fibre Tech, fibreglass
coatings for swimming pools. The following chart was included in a brochure. Is the comparison
fair? What is the scale for the vertical axis? Is the scale in dollars or in percent?
Fibre Tech Reduces Chemical Use, Saving You Time and Money.
• Saves up to 60 percent on chemical costs alone.
• Reduces water loss, which means less need to replace chemicals and up to 10-
percent warmer water (reducing heating costs, too).
• Fibre Tech pays for itself in reduced maintenance and chemical costs.
Misleading information may be given by an improper scaling used in a chart or
graph where an attempt is made to change all the dimensions simultaneously in
response to a change in one-dimensional data.
YOUR SAVINGS
Beauty
That Lasts
Less
Maintenance
Reduced
Chemical Use
ULTRA © DISTANCE
DUNLOP © DDH IV
MAXFLI MD ©
TITLEIST © HVC
TOP-FLITE © Tour 90
TOP-FLITE © MAGNA
540.4 m
534.3 m
522.1 m
520.3 m
517.2 m
515.8 m
Combined yardage with a driver, #5 iron, and #9 iron,
Ultra Distance is clearly measurably longer.
Again, we caution you. When you see a chart or graph, particularly as part of an
advertisement, be careful. Look at the scales used on the x-axis and the y-axis.
Guidelines for Selecting a Graph to Summarize Data
Bar and pie charts both are used to display qualitative data (single data series).
Generally, a bar chart is preferred to display a single data series because it is easier to
visualize changes within a data set. According to psychologists who have studied visual
preferences,3 it is more complicated to interpret the relative size of angles in a pie chart
than to judge the length of the rectangles in a bar chart.
To compare two or more qualitative data sets, both clustered bar charts and stacked
bar charts are used; however, in the case of stacked bar charts, it is difficult to compare
data visually due to the floating baselines of rectangles that are stacked on the
bottom rectangles.
The histogram is a more popular graphic to summarize a large, quantitative, singledata
set. It is not used to compare two or more quantitative data series. Instead, frequency
polygons, cumulative frequency polygons and line charts are used to compare
two or more data series in a single graphic frame. The stem-and-leaf display is very
convenient for mid-sized quantitative data.
EXERCISES 2-23 TO 2-28
2-23. A small-business consultant is investigating the performance of several companies.
The sales in 2000 (in thousands of dollars) for the selected companies are
listed below. The consultant wants to include a chart in a report comparing the
sales of the six companies. Use a bar chart to compare the fourth-quarter sales
of these corporations and write a brief report summarizing the bar chart.
Corporation Fourth-Quarter Sales
($ thousands)
Hoden Building Products 1 645.2
J & R Printing, Inc. 4757.0
Long Bay Concrete Construction 8 913.0
Mancell Electric and Plumbing 627.1
Maxwell Heating and Air Conditioning 24 612.0
Mizella Roofing & Sheet Metal 191.9
DATA
Qualitative Data Quantitative Data
Bar Chart
Pie Chart
Clustered Bar Chart
Stacked Bar Chart
(usually for a single data series)
(single data series)
(two or more data series)
(two or more data series)
Histogram
Cumulative Frequency Polygon
Line Chart
Frequency Polygon
Stem-and-Leaf Display
(single data series)
(one or more data series)
(one or more data series)
(single, mid-sized data series)
Describing Data: Frequency Distributions and Graphic Presentation 69
70 Chapter Two
2-24. The Gentle Corporation in Montreal, Quebec sells fashion apparel for men and
women and a broad range of other related products. It serves customers in the
United States and Canada by mail. Listed below are the net sales from 1996 to
2001. Draw a line chart depicting the net sales over the period.
Year Net Sales
($ millions)
1996 525.00
1997 535.00
1998 600.50
1999 625.80
2000 645.70
2001 758.75
2-25. The following are long-term business credit amounts ($millions) from 1996 to
2000 (Canada). Draw a line chart depicting the long-term business credit for
the period.
Year Long-Term
Business Credit
($ millions)
1996 357 946
1997 392 846
1998 432 909
1999 470 250
2000 504 850
Source: Adapted from Statistics
Canada, Bank of Canada, CANSIM,
Matrix 2567
2-26. The following are the unemployment rates in Canada from 1996 to 2000.
Draw a line chart for the unemployment rate for the period 1996 to 2000.
Describe the trend for the unemployment rate.
Year Unemployment
Rate (%)
1996 9.6
1997 9.1
1998 8.3
1999 7.6
2000 6.8
Source: Adapted from Statistics Canada,
CANSIM, Matrix 3472; and Catalogue
No. 71-529-XPB
2-27. The following are gross domestic products (GDP) at market prices from 1990 to
2000. Draw a line chart to show the highest and lowest GDP at market prices.
Year GDP at market prices
($ millions)
1990 705464
1991 692 247
1992 698 544
1993 714 583
1994 748 350
1995 769 082
1996 780 916
1997 815 013
1998 842 002
1999 880 254
2000 921 485
Source: The Centre for the Study of Living
Standards: www.csls.ca
2-28. The following table shows the gross domestic product (GDP) for eight countries
in 2000. Develop a bar chart and summarize the results.
Country GDP
($ trillions)
USA 9.3
Japan 3.9
Germany 2.2
France 1.5
UK 1.4
Italy 1.2
Canada 0.7
Chapter Outline
I. A frequency distribution is a grouping of data into mutually exclusive categories
showing the number of observations in each category.
A. The steps in constructing a frequency distribution are:
1. Decide how many classes you need.
2. Determine the class width or interval.
3. Set the individual class limits.
4. Tally the raw data into classes.
5. Count the number of tallies in each class.
B. The class frequency is the number of observations in each class.
C. The class interval is the difference between the lower limit and the upper
limit of a class.
D. The class midpoint is halfway between the lower limit and the upper limit
of a class.
Describing Data: Frequency Distributions and Graphic Presentation 71
72 Chapter Two
II. A relative frequency distribution shows the fraction of the observations in each
class.
III. A stem-and-leaf display provides a frequency distribution of a data set and at
the same time shows a graphic similar to a histogram.
A. The leading digit is the stem and the trailing digits are the leaves.
B. The advantages of the stem-and-leaf display over a frequency distribution
include:
1. The identity of each observation is not lost.
2. The digits themselves give a picture of the distribution.
IV. There are two methods for graphically portraying a frequency distribution.
A. A histogram portrays the number of frequencies in each class in the form of
rectangles.
B. A frequency polygon consists of line segments connecting the points formed
by the intersections of the class midpoints and the class frequencies.
V. A cumulative frequency polygon shows the number of observations below
a certain value.
Chapter Exercises 2-29 to 2-51
2-29. A data set consists of 83 observations. How many classes would you
recommend for a frequency distribution?
2-30. A data set consists of 145 observations that range from 56 to 490. What size
class interval would you recommend?
2-31. The following is the number of minutes it takes to commute from home to
work for a group of automobile executives.
28 25 48 37 41 19 32 26 16 23 23 29 36
31 26 21 32 25 31 43 35 42 38 33 28
(a) How many classes would you recommend?
(b) What class interval would you suggest?
(c) What would you recommend as the lower limit of the first class?
(d) Organize the data into a frequency distribution.
(e) Comment on the shape of the frequency distribution.
2-32. The following data are the weekly amounts (in dollars) spent on groceries for
a sample of households. This data is also found on the accompanying CD in
Exercise 2-32.xls.
271 363 159 76 227 337 295 319 250 279 205 279
266 199 177 162 232 303 192 181 321 309 246 278
50 41 335 116 100 151 240 474 297 170 188 320
429 294 570 342 279 235 434 123 325
(a) How many classes would you recommend?
(b) What class interval would you suggest?
(c) What would you recommend as the lower limit of the first class?
(d) Organize the data into a frequency distribution.
2-33. The following stem-and-leaf display shows the number of minutes spent per
week, watching daytime TV for a sample of university students.
2 0 0 5
3 1 0
6 2 1 3 7
10 3 0 0 2 9
13 4 4 9 9
24 5 0 0 1 5 5 6 6 7 7 9 9
30 6 0 2 3 4 6 8
(7) 7 1 3 6 6 7 8 9
33 8 0 1 5 5 8
28 9 1 1 2 2 3 7 9
21 10 0 2 2 3 6 7 8 9 9
12 11 2 4 5 7
8 12 4 6 6 8
4 13 2 4 9
1 14 5
(a) How many students were studied?
(b) How many observations are in the second class?
(c) What is the smallest value? the largest value?
(d) List the actual values in the fourth row.
(e) How many students watched less than 60 minutes of TV?
(f) How many students watched 100 minutes or more of TV?
(g) What is the middle value?
(h) How many students watched at least 60 minutes but less than
100 minutes?
2-34. The following stem-and-leaf display reports the number of orders received per
day by a mail-order firm.
1 9 1
2 10 2
5 11 2 3 5
7 12 6 9
8 13 2
11 14 1 3 5
15 15 1 2 2 9
22 16 2 2 6 6 7 7 8
27 17 0 1 5 9 9
(11) 18 0 0 0 1 3 3 4 6 7 9 9
17 19 0 3 3 4 6
12 20 4 6 7 9
8 21 0 1 7 7
4 22 4 5
2 23 1 7
(a) How many days were studied?
(b) How many observations are in the fourth class?
(c) What is the smallest value and what is the largest value?
Describing Data: Frequency Distributions and Graphic Presentation 73
74 Chapter Two
(d) List the actual values in the sixth class.
(e) How many days did the firm receive less than 140 orders?
(f) How many days did the firm receive 200 or more orders?
(g) On how many days did the firm receive 180 orders?
(h) What is the middle value?
2-35. The following histogram shows the scores on the first statistics exam.
(a) How many students took the exam?
(b) What is the class interval?
(c) What is the class midpoint for the first class?
(d) How many students earned a score of less than 70?
2-36. The following chart summarizes the selling price of homes sold last month in
Victoria, B.C.
(a) What is the chart called?
(b) How many homes were sold during the last month?
(c) What is the class interval?
(d) About 75 percent of the homes sold for less than what amount?
(e) 175 of the homes sold for less than what amount?
2-37. A chain of ski and sportswear shops catering to beginning skiers, headquartered
in Banff, Alberta, plans to conduct a study of how much a beginning skier
spends on his or her initial purchase of equipment and supplies. Based on
these figures, they want to explore the possibility of offering combinations,
such as a pair of boots and a pair of skis, to induce customers to buy more.
A sample of their cash-register receipts revealed these initial purchases
(in dollars):
140 82 265 168 90 114 172 230 142 86 125 235
212 171 149 156 162 118 139 149 132 105 162 126
216 195 127 161 135 172 220 229 129 87 128 126
175 127 149 126 121 118 172 126
50
100
150
200
250
0 50 100 150 200 250 300 350
Selling price ($000)
25
50
75
100
Frequency
Percent
0
5
10
15
20
25
50 60 70 80 90 100
Frequency
Score
(a) Arrive at a suggested class interval. Use five classes, and let the lower limit
of the first class be $80.
(b) What would be a better class interval?
(c) Organize the data into a frequency distribution.
(d) Interpret your findings.
2-38. The numbers of shareholders for a selected group of large companies
(in thousands) are listed in Exercise 2-38.xls on the CD-ROM accompanying
the text.
The numbers of shareholders are to be organized into a frequency
distribution and several graphs drawn to portray the distribution.
(a) Using seven classes and a lower limit of 130, construct a frequency
distribution.
(b) Portray the distribution in the form of a frequency polygon.
(c) Portray the distribution in a less than cumulative frequency polygon.
(d) Based on the polygon, three out of four (75 percent) of the companies have
how many shareholders or fewer?
(e) Write a brief analysis of the number of shareholders based on
the frequency distribution and graphs.
2-39. The following is the list of top-selling drugs in 2002. Draw an appropriate chart
to portray the data.
Products Sales
($ billions)
Lipitor (cholesterol-reducing) 5.7
Zocor (cholesterol-reducing) 5.3
Claritin-family (anti-histamine) 4.2
Norvasc (calcium-antagonist) 4.1
Losec (anti-ulcerant) 3.6
2-40. The Midland National Bank selected a sample of 40 student chequing accounts.
Below are their end-of-the-month balances.
404 74 234 149 279 215 123 55 43 321 87 234
68 489 57 185 141 758 72 863 703 125 350 440
37 252 27 521 302 127 968 712 503 489 327 608
358 425 303 203
(a) Tally the data into a frequency distribution using $100 as a class interval
and $0 as the starting point.
(b) Draw a cumulative frequency polygon.
(c) The bank considers any student with an ending balance of $400 or more
a “preferred customer.” Estimate the percentage of preferred customers.
(d) The bank is also considering a service charge to the lowest 10 percent of
the ending balances. What would you recommend as the cut-off point
between those who have to pay a service charge and those who do not?
2-41. The following are grades of students in Math 1021 in 2002.
57 81 47 87 21 47 57 64 86 41 84 48 80 58 88
73 30 64 84 77 28 95 40 42 10 72 61 13 56 47
55 48 60 99 88 86 95 49
Describing Data: Frequency Distributions and Graphic Presentation 75
76 Chapter Two
(a) Construct a stem-and-leaf display.
(b) Summarize your conclusion.
2-42. A recent study of home technologies reported the number of hours of personal
computer usage per week for a sample of 60 persons. Excluded from the study
were people who worked out of their homes and used the computer as a part of
their work.
9.3 5.3 6.3 8.8 6.5 0.6 5.2 6.6 9.3 4.3 6.3 2.1 2.7 0.4
3.7 3.3 1.1 2.7 6.7 6.5 4.3 9.7 7.7 5.2 1.7 8.5 4.2 5.5
5.1 5.6 5.4 4.8 2.1 10.1 1.3 5.6 2.4 2.4 4.7 1.7 2.0 6.7
1.1 6.7 2.2 2.6 9.8 6.4 4.9 5.2 4.5 9.3 7.9 4.6 4.3 4.5
9.2 8.5 6.0 8.1
(a) Organize the data into a frequency distribution. How many classes would
you suggest? What value would you suggest for a class interval?
(b) Draw a histogram. Interpret your result.
2-43. Merrill Lynch recently completed a study regarding the size of investment
portfolios (stocks, bonds, mutual funds, and certificates of deposit)
for a sample of clients in the 40 to 50 age group. Listed below are the values
of all the investments for the 70 participants in the study.
669.9 7.5 77.2 7.5 125.7 516.9 219.9 645.2
301.9 235.4 716.4 145.3 26.6 187.2 315.5 89.2
36.4 616.9 440.6 408.2 34.4 296.1 185.4 526.3
380.7 3.3 363.2 51.9 52.2 107.5 82.9 63.0
228.6 308.7 126.7 430.3 82.0 227.0 321.1 403.4
39.5 124.3 118.1 23.9 352.8 156.7 276.3 23.5
31.3 301.2 35.7 154.9 174.3 100.6 236.7 171.9
221.1 43.4 212.3 243.3 315.4 5.9 1002.2 171.7
295.7 437.0 87.8 302.1 268.1 899.5
(a) Organize the data into a frequency distribution. How many classes would
you suggest? What value would you suggest for a class interval?
(b) Draw a histogram. Interpret your result.
2-44. The following are gross domestic products (GDP) per head in the following
European countries (in dollars). Develop a bar chart depicting this information.
Country GDP per head
($)
Austria 26 740
Denmark 32 576
France 24 956
Germany 27 337
Greece 11 860
Norway 35 853
Turkey 3 120
2-45. Care Heart Association reported the following percentage breakdown of
expenses. Draw a pie chart depicting the information. Interpret the results.
Category Percent
Research 32.3
Public Health Education 23.5
Community Service 12.6
Fundraising 12.1
Professional and Educational Training 10.9
Management and General 8.6
2-46. In its 2002 annual report, Schering-Plough Corporation reported the income,
in millions of dollars, for 1995 to 2002 as listed below. Develop a line chart
depicting the results and comment on your findings.
Year Income
($ millions)
1995 1053
1996 1213
1997 1444
1998 1756
1999 2110
2000 2900
2001 3595
2002 4550
2-47. The following table shows Canada’s exports in merchandise trade with its
principal trading partners:
Principal December 1999 December 2000
Trading Partner ($ millions) ($ millions)
USA 27 243 31 876
Japan 764 824
European Union 1 616 1 896
Other OECD Countries 728 682
All Other Countries 1 510 1 572
Source: Adapted from Statistics Canada, CANSIM, Matrix 3618
(a) Draw a clustered bar graph.
(b) Name the trading partner to whom we exported more than any other
trading partner in 2000.
2-48. The following is the population distribution of Canada by sex from 1996 to
2000. Draw a stacked bar graph and comment on your findings.
Year Male Female
1996 14 691 777 14 980 115
1997 14 850 874 15 136 340
1998 14 981 482 15 266 467
1999 15 104 717 15 388 716
2000 15 232 909 15 517 178
Source: Adapted from Statistics Canada, CANSIM, Matrix 6213
Describing Data: Frequency Distributions and Graphic Presentation 77
78 Chapter Two
2-49. Cash receipts from milk and cream sold from farms in six provinces in 2001
are given below. Draw a pie chart to display the data set.
Province Cash Receipts
($ thousands)
Alberta 318 454
B.C. 336 977
Manitoba 154 029
N.B. 69 041
Nova Scotia 90 368
P.E.I. 50 987
Source: Adapted from Statistics Canada, CANSIM,
Matrices 5650–5651; and Catalogue No. 23-001-XIB
2-50. The following are exports of goods to the Organization for Economic
Co-operation and Development (OECD4) from 1995 to 2000. Draw a line
chart and describe the trend in exports of goods to the OECD.
Year Export of Goods
($ millions)
1995 4563.4
1996 5087.8
1997 8033.5
1998 7560.4
1999 7160.9
2000 8159.3
Source: Adapted from Statistics Canada, CANSIM,
Matrices 3651 and 3685
2-51. The following table shows the volume (in kilolitres) of milk and cream sold
from farms in 2001 in six Canadian provinces. Draw a simple bar chart to
depict the data.
Province Volume of
Milk and Cream
Sold from Farms
(kL)
NFLD 33 583
P.E.I. 94 472
Nova Scotia 173 985
N.B. 134 428
Manitoba 294 674
Alberta 208 198
Source: Adapted from Statistics Canada, CANSIM,
Matrices 5650–5651; and Catalogue No. 23-001-XIB
WWW.exercises.ca 2.52 to 2.53
2-52. Go to the Web site: www.statcan.ca. Click English, Canadian Statistics,
Education, Graduates, and Secondary School Graduates. Draw a bar chart
depicting the number of school graduates in each province. Summarize your
findings.
2-53. Go to the Statistics Canada Web site (www.statcan.ca) and click English/
Canadian Statistics / Labour, Employment, and Unemployment /Earnings.
Select two data series for a given category and draw a clustered bar graph.
Computer Data Exercises 2-54 to 2-57
2-54. The file Exercise 2-32.xls contains the amount spent on groceries by
households.
(a) How many classes would you recommend?
(b) What class interval or width would you suggest?
(c) Organize the data into a frequency distribution.
(d) Use Excel to draw a histogram. Use the number of classes you
recommended. Describe the shape of the histogram.
(e) Draw the histogram using Excel. Let Excel decide the number of classes.
Describe the shape of the histogram.
2-55. Use the data in the file Exercise 2-32.xls to draw a stem-and-leaf diagram. Use
Minitab. Use the same data to draw a histogram. Do you find the stem-and-leaf
diagram more informative than the histogram? Explain.
2-56. Refer to the OECD data on the CD, which reports information on census,
economic, and business data for 29 countries. Develop a stem-and-leaf diagram
for the variable regarding the percentage of the workforce that is over 65 years
of age. Are there any outliers? Briefly describe the data.
2-57. The file Exercise 2-57.xls contains the amount of money spent by beginning
skiers on the purchase of equipment and supplies.
(a) Draw a cumulative frequency polygon using Excel. Do not specify the Bin.
(b) Estimate the proportion of the amount of money spent on the purchase of
equipment and supplies that is less than $143.
(c) How many skiers spent less than $173.50 on the purchase of equipment
and supplies?
(d) Draw a suitable graph to summarize the data.
Describing Data: Frequency Distributions and Graphic Presentation 79
80 Chapter Two
CHAPTER 2 Answers to self-review
2-1. (a) The raw data.
(b) Commission Number of
Salespeople
1400 up to 1500 2
1500 up to 1600 5
1600 up to 1700 3
1700 up to 1800 1
Total 11
(c) Class frequencies.
(d) The largest concentration of commissions is in
the class $1500 up to $1600. The smallest commission
is about $1400 and the largest is about
$1800.
2-2. (a) 5, (24 16, less than 24, and 25 32, more
than 24. Hence, k 5 is suggested).
(b) 10, found by rounding up .
(c) Class Frequency
23 up to 33 3
33 up to 43 1
43 up to 53 3
53 up to 63 9
63 up to 73 8
Total 24
2-3. (a) 21
(b) 26.3 percent
(c) 17.5 percent (found by (0.1 0.05 0.025)
100)
2-4. 7 7
8 0 0 1 3 4 8 8
9 1 2 5 6 6 8 9
10 1 2 4 8
11 2 6
(a) 8
(b) 10.1, 10.2, 10.4, 10.8
(c) 11.6 and 7.7
2-5. (a)
(b)
(c) The smallest annual sales volume of imports by
a supplier is about $2 million, the highest about
$17 million. The concentration is between $8
million and $11 million.
2-6. (a) A frequency distribution.
(b) Annual Net Profits Cumulative
($000) Number
65 up to 75 1
75 up to 85 7
85 up to 95 14
95 up to 105 26
105 up to 115 31
115 up to 125 34
0
10
20
30
40
2 5 8 11 14 17
Percent of total
Imports ($ millions)
0
5
10
15
20
2 5 8 11 14 17
Number of suppliers
Imports ($ millions)
6
13
20
10
1
71 25
5
9 2






.
(c)
The number of companies with annual net profits
of less than $105 000 is about 26.
2-7. (a)
(b) Chartered banks provided 66 percent of
the total consumer credit, Special Purpose
Corporations provided 16 percent of the total
consumer credit, and so on.
Consumer Credit
7%
16%
66%
2%
Chartered Banks
Trust and
Mortgage
Life Insurance
Companies
Special Purpose
Corporations
Finance Companies
8%
1%
Credit Unions
5
10
15
20
25
30
35
65 75 85 95 105 115 125
Describing Data: Frequency Distributions and Graphic Presentation 81