Social-studies Textbooks (3)

Is there a relationship between gender and fear of walking alone at night (fear), support for capital punishment ( cappun , and job satisfaction (satjob)? Are men or women more likely to say that there is a place nearby where they are afraid to walk at night? Which gender is more supportive of the death penalty? Are men or women more satisfied with their jobs (satjob)? We will use the Crosstabs procedure, with chi square and column percentages to explore this relationship. Click the SPSS icon on your desktop. Load the GSS2012 database. Click Analyze Descriptive Crosstabs. Find fear, cappun, and satjob in the list of variables and move them into the "Rows" box. Find sex in the list of variables and move it into the "Columns" box. Click the Statistics button and select Chi-square. Return to the "Crosstabs" window, click the Cells button, and select Column in the "Percentages" box.

What area of law was a common subject of the decisions in Mapp v. Ohio, Gideon v. Wainwright, Escobedo v. Illinois, and Miranda v. Arizona? A. due process in criminal cases B. equal rights C. equal representation D. federal versus state power

Fifteen individuals were randomly selected from the respondents to a public opinion survey, and their scores are reproduced here. a. Calculate Pearson's \(r\) for age \((X)\) and four dependent variables \(\left(Y^{\prime} s\right):\) prestige, number of children, support for abortion, and hours of TV watching. b. Calculate Pearson's \(r\) for gender \((X)\) and four dependent variables \(\left(Y^{\prime} s\right):\) support for abortion, prestige, hours of TV watching, and number of children. c. Test the four relationships in either \(a\) or \(b\) for significance. $$ \begin{array}{cccccc} \begin{array}{c} \text { Occupational } \\ \text { Prestige } \end{array} & \begin{array}{c} \text { Number } \\ \text { of } \\ \text { Children } \end{array} & \text { Age } & \begin{array}{c} \text { Support for } \\ \text { Legal Abortion } \end{array} & \begin{array}{c} \text { Hours of } \\ \text { TV per } \\ \text { Day } \end{array} & \text { Gender } \\ \hline 32 & 3 & 34 & 3 & 1 & 1 \\ 50 & 0 & 41 & 1 & 3 & 1 \\ 17 & 0 & 52 & 5 & 2 & 1 \\ 69 & 3 & 67 & 1 & 5 & 0 \\ 17 & 0 & 40 & 1 & 5 & 0 \\ 52 & 0 & 22 & 2 & 3 & 1 \\ 32 & 3 & 31 & 3 & 4 & 0 \\ 50 & 0 & 23 & 4 & 4 & 0 \\ 19 & 9 & 64 & 1 & 6 & 1 \\ 37 & 4 & 55 & 4 & 2 & 0 \\ 14 & 3 & 66 & 5 & 5 & 1 \\ 51 & 0 & 22 & 2 & 0 & 0 \\ 45 & 0 & 19 & 3 & 7 & 0 \\ 44 & 0 & 21 & 4 & 1 & 1 \\ 46 & 4 & 58 & 2 & 0 & 1 \end{array} $$