Does the position on the death penalty depending on gender? One question on the survey asked, “Do you favor or oppose the death penalty for convicted murderers?

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Instructions: You will analyze data from “GSS-93 Project 4.xlsx”, posted in Canvas and emailed to you. It contains data from a 1993 nationwide survey of American adults, randomly chosen. Assume that these responses comprise a representative sample of all American adults that year.   Use the Crunch It! software that is part of Sapling to conduct the analyses. Include all output produced in your report.

** Select InsertpRandom NumberspUniform, then input 0 for Minimum, 1 for Maximum, 808 for Samples, then click the Samples button. A new column of numbers is added to the data set.   Move your mouse to the variable name for this column, click the down arrow, then choose Sort Ascending. Scroll down to the last case, click to the left of the row number to select it, then choose FilteringpExclude Selected. Repeat these instructions to exclude the last eight cases (801-808). Be sure to complete both parts a) and b) with these same eight cases excluded so the output matches.

1. Does the position on the death penalty depending on gender? One question on the survey asked, “Do you favor or oppose the death penalty for convicted murderers?” You will conduct a test of the following hypotheses:

H0: There is no association between position on death penalty and gender vs. Ha: There is an association

a) Conduct a Chi-Square test of association. Choose StatisticspContingency Tablepget frequencies. In the dialog box, specify “sex” as the row variable and “cappun” as the column variable. Click Calculate. Report the test statistic, degrees of freedom, and the P-value. Is there evidence of an association? Justify (use α œ 0.0&). If so, identify which group (males or females) is more likely to favor the death penalty (use row %'s).

b) Let :1 = proportion of adult Amer. males who favor the death penalty, and define:2 similarly for adult Amer. 

2. Is there an association between the frequency of television viewing and the age of the respondent? One question on the survey asked, “How many hours of TV do you view in a typical day?” I've grouped the responses into three age categories: 1 - '18-24 yrs. old';  2 - '25-49 yrs. old';  3 - '50 years or older.

Let µ3 œ mean a number of viewing hours of response group 3 Ð3 œ 1ß 2ß $Ñ. The hypotheses we will consider are

H0:µ1 œ µ2 œ µ$vs. Ha: At least one of the µ3's differs from the others

Either repeat step "**" above or continue working with the same eight cases excluded. Next, choose

FilteringpExclude... and exclude rows where tv hours > 10 (some large responses don't seem reasonable).

a) Create side-by-side Box Plot graphs of viewing hours (tvhours) by age group (agegrp) [GraphicspBoxPlotpGrouped, with Y-label "TV viewing per day (hours)"]. Do the box plots indicate an association between the frequency of viewing TV and age? Which hypothesis does your conclusion coincide with?

b) Carry out a one-way ANOVA test (StatisticspANOVApOne-waypGrouped, Data: tvhours, Group by: agegrp).

Report the test statistic ("F-value") and P-value for the test of H0: µ1 œ µ2 œ µ$. Using α œ 0.0&, state your conclusion about this null hypothesis. Is there evidence of an association between the frequency of viewing TV and age?

c) Choose StatisticspDescriptive StatisticspGrouped (Data: tvhours, Group by: agegrp), then report viewing habits by ordering the sample means. Now conduct pairwise comparisons of the three age groups. Choose Statistics t p2- samples grouped to produce three 95% confidence intervals (each must be done in a separate step):

i) 18-24 vs. 25-49 (µ1- µ2) ii) 18-24 vs. 50+   (µ1 - µ$) iii) 25-49 vs. 50+ (µ2 - µ$)

Note which confidence intervals indicate a significant difference in means (justify your choices). For those who indicate a significant difference, report the difference in sentence form using the confidence interval bounds.

Finally, explain in simple words the nature of the relationship between the frequency of viewing TV and age. What might be the reason for this relationship?

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