Class Project VI: Memorandum on Bivariate Data Analysis Part I
Somewhat recent research (see Payne et al., 2004; Unnever & Cullen, 2007) has examined demographic correlates of support for capital punishment, across a variety of contexts. These studies have found that, among others, two of the more salient predictors of support for capital punishment are sex and race. While certainly making consequential contributions to the literature on punitiveness in general and capital punishment in particular, these studies have some limitations. (The former study relies on a nonrepresentative sample, and the latter study employs the use of data over fifteen years old.)
In this project, practicum students will address both of the aforementioned limitations of previous studies in this area by employing recent (2018), nationally-representative data to explore demographic correlates of attitudes toward capital punishment. As a student of a methods/stats course in the social sciences you are well-positioned to investigate this matter by employing the most robust source for trend data on American attitudes across the social/political spectrum: The 2018 General Social Survey
The 2018 GSS contains a host of variables that will allow researchers to assess the null hypothesis that there is no relationship between demographic variables (in this case, sex and race) and support for capital punishment. In particular, you are to investigate the potential link between sex and support for capital punishment (are there any differences between males and females in support for the death penalty), and race and support for capital punishment (are there any differences between whites and nonwhites in their support for the death penalty?). It just so happens that you have recently acquired the requisite skills to properly assess if these relationships are in fact significant – and if so, what is the direction of the relationship (e.g., are males and whites more or less likely than females and nonwhites to support capital punishment?)?
There are three variables that students will use in a condensed version of the 2018 GSS – REDUCED 2018 GSS — that I have created specifically for this project. While I do not specify the independent and dependent variables in this analysis, I would like to think that after nearly one year of research methodology, students should be able to figure this one out on their own. The three variables, which are provided near the bottom of the dataset (variable view in SPSS) are:
Given the level of measurement of these three measures (students should know levels of measurement by now, but keep in mind that all three are measured on the same level), your instructor thinks it best if you employ the use of the crosstabulations procedure in SPSS (analyze/descriptive statistics/crosstabs). Based on your analyses, students should answer the following questions in full.
There will be two separate assignment drop boxes created in Canvas: syntax drop box, and Class Project VI drop box. Students should include the syntax files for all procedures used.
While there is no specific length/page requirement to this assignment, students are asked to answer the questions comprehensively. Assignments MUST be typed, with 1” margins throughout the document. All students must use 12-point, Times New Roman Font. Students should single-space within each answer (including the letters – e.g., 1a, 1b), but double space between answers (e.g., 1, 2, 3).
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