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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- Frequency, Frequency distribution, Histogram