c.
Construct a bar chart for these data.
6.
A recent survey asked 5,324 individuals: “What’s most
important to you when choosing where to live?”
The
responses are shown in the following relative frequency
distribution.
S
OURCE
: CNNMoney.com, July 13, 2010.
Response
Relative Frequency
Good jobs
0.37
Afordable homes
0.15
Top schools
0.11
Low crime
0.23
Things to do
0.14
a.
Construct the corresponding frequency distribution.
How many of the respondents chose “low crime” as
the most important criteria when choosing where
to live?
b.
Construct a bar chart for these data.
7. What is the perfect summer trip? A National Geographic Kids survey ( AAA Horizons, April 2007) asked this question
to 316 children ages 8 to 14. Their responses are given in the
following frequency distribution.
Top Vacation Choice
Frequency
Cruises
140
Beaches
68
Amusement Parks
68
Big Cities
20
Lakes
12
Summer Camp
8
a.
Construct a relative frequency distribution. What
percentage of the responses cited “Cruises” as the perfect
summer trip?
b.
Construct a bar chart for these data.
8.
The following table lists U.S. revenue (in $ billions) of the
major car-rental companies.
S
OURCE
:
The Wall Street Journal
, July 30, 2010.
Car-Rental Company
Revenue in 2009
Enterprise
$10.7
Hertz
4.7
Avis Budget
4.0
Dollar Thrifty
1.5
Other
1.0
a.
Construct a relative frequency distribution.
b.
Hertz accounted for what percentage of sales?
c.
Construct a pie chart for these data.
9.
A survey conducted by CBS News asked 829 respondents
which of the following events will happen irst. The
responses are summarized in the following table:
S
OURCE
:
Vanity Fair,
December 2009.
Cure for cancer found
40%
End of dependence on oil
27%
Signs of life in outer space
12%
Peace in Middle East
8%
Other
6%
None will happen
7%
kel73664_ch02_016-051.indd
24
11/22/11
4:59 PM

CHAPTER 2
Tabular and Graphical Methods
B U S I N E S S S T A T I S T I C S
25
2.2
Summarizing Quantitative Data
With quantitative data, each value is a number that represents a meaningful amount or
count. The number of patents held by pharmaceutical irms (count) and household in-
comes (amount) are examples of quantitative data. Although different in nature from
qualitative data, we still use frequency distributions to summarize quantitative data.
Before discussing the mechanics of constructing a frequency distribution, we ind it
useful to irst examine one in its inal form, using the house-price data from Table 2.1.
We converted the raw data (the actual values) from Table 2.1 into a frequency distribu-
tion with ive intervals or
classes
, each of width 100, as shown in Table 2.7. We see, for
instance, that four houses sold in the irst class, where prices ranged from $300,000 up to
$400,000. The data are more manageable using a frequency distribution, but some detail
is lost because we no longer see the actual values.
Class (in $1000s)
Frequency
300 up to 400
4
400 up to 500
11
500 up to 600
14
600 up to 700
5
700 up to 800
2
Total
5
36
TABLE 2.7
Frequency Distribution for House-Price Data
LO
2.3
Summarize
quantitative
data by
forming
frequency
distributions.

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