Application

Now that you have completed all of the activities in this chapter, use the concepts and techniques that you've learned to respond to these questions. For each question, explain which test you've chosen, report the relevant test results, and interpret the results in the context of the scenario.

  1. Scenario: Before we leave the pipeline data, let's ask two more questions:

    1. Are disruptions equally likely to occur in all regions of the United States?

    2. Are the variables Explosion and LRTYPE_TEXT independent?

    3. Are the variables Region and Explosion independent?

  2. Scenario: The main example in Chapter 5 was based on the data table called Dolphins. Please note that this data table contains frequencies rather than raw data; refer to Figure 5.2 for instructions about creating the contingency table.

    1. Are the variables Activity and Period independent?

    2. Are dolphins equally likely to be observed feeding, socializing, and traveling? (Again, recall that the data table shows frequencies rather than raw data.)

  3. Scenario: We'll continue to examine the World Development Indicators data in BirthRate 2005. We'll focus on three categorical variables in the data table.

    • Region: Global region of the country in question

    • Provider: Source of maternity leave benefits (public, private, or a combination of both)

    • MatLeave90+: Mandated length of maternity leave—fewer than 90 days, or 90 days and more

    1. Are the variables Provider and Region independent?

    2. Are the variables Provider and MatLeave90+ independent?

    3. Are the variables MatLeave90+ and Region independent?

  4. Scenario: In these questions, we return to the NHANES data table containing survey data from a large number of people in the U.S. in 2005. For this analysis, we'll focus on just the following variables:

    • RIDRETH1: Respondent's racial or ethnic background

    • DMDMARTL: Respondent's reported marital status

    1. Are these two categorical variables independent?

  5. Scenario: The following questions were inspired by a 2009 article on alcohol consumption and risky behaviors (Hingson et al. 2009) based on responses to a large national survey. The data table BINGE contains summary frequency data calculated from tables provided in the article. We'll focus on the self-reported frequency of binge drinking (defined as five or more drinks in a two-hour period for males and four or more drinks in a two-hour period for females) and whether the respondents reported having ever been involved in a car accident after drinking.

    1. Are the two variables independent? Explain.

  6. Scenario: Let us once again look at the Sleeping Animals data table.

    1. Are mammal species equally likely to be classified across the five categories of the exposure index?

    2. Are all mammal species equally likely to be classified across the five categories of the predation index?

    3. Are the variables Predation and Exposure independent? Explain.

  7. Scenario: For these questions we return to the TimeUse data table. Use the data filter to confine the analysis to the responses from 2007.

    1. Are employment status and gender independent? Explain.

    2. Are employment status and region independent? Explain.

    3. Are employment status and marital status independent? Explain.

    4. Are marital status and gender independent? Explain.

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