Chapter 2: 2.4 (page 40)
Provide a reason why the classification of data is important
Short Answer
Data classification eases the access & integrity of data; improves its analysis, interpretation & presentation of data.
Chapter 2: 2.4 (page 40)
Provide a reason why the classification of data is important
Data classification eases the access & integrity of data; improves its analysis, interpretation & presentation of data.
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San Francisco Giants. From the Baseball Almanac website, we found the heights, in inches, of the players on the 2012 World Series-winning San Francisco Giants baseball team.

a. Construct a stem-and-leaf diagram of these data with five lines per stem.
b. Why is it better to use five lines per stem here instead of one or two lines per stem?
Top 10 Green Cars. The following table presents information on the Kelley Blue Book's "10 Best Green Cars of 2013." Note that mpg and mpge are abbreviations for miles per gallon and miles per gallon equivalent, respectively. Identify the type of data provided by the information in each column of the table. [SOURCE: "10 Best Green Cars of 2013." Published by the Kelley Blue
Construct a stem-and-leaf diagram for the data, using one line per stem.

Standard Normal Distribution. One of the most important distributions in statistics is the standard normal distribution. We discuss this distribution in detail in Chapter 6.
a. Use the technology of your choice to generate a sample of 3000 observations from a variable that has the standard normal distribution.
b. Use the technology of your choice to get a relative-frequency histogram for the 3000 observations that you obtained in part (a).
c. Based on the histogram you obtained in part (b), what specific shape does the standard normal distribution have? Explain your reasoning.
High School Completion. As reported by the U.S. Census Bureau in Educational Attainment in the United States, the percentage of adults in each state and the District of Columbia who has completed high school is provided on the WeissStats site.
a. use the technology of your choice to identify the modality and symmetry (or non-symmetry) of the distribution of the data set.
b. if unimodal, classify the distribution as symmetric right-skewed. or left-skewed.
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