Choose five variables from the GSS 2018 data set: choose one nominal variable, one ordinal variable, and three scale variables.
1. Go to the website http://gss.norc.org/Get-Documentation and explore your variables in detail.
Try to find out as much information as you can for your variables. This means you should explore the codebook and/or website and find out as much information about your variables as possible (e.g. What was the exact question on the survey? What did it measure? How did it measure? (labels, values, etc.).
2. You will need all this information for the introduction about your variables in your research report. (Introduction of your paper).
3. Prepare a frequency distribution for each variable (Save the output, copy what you need into a word document and label it accordingly; format the SPSS output to make it consistent with the formatting in the textbook – we talked about in class, i.e. number, caption, etc.) (Not needed. Purchaser will complete this portion.)
4. Create the appropriate statistical figure. That is, create a histogram, bar graph, or frequency polygon of each of your variables. Save the output in a word document and format your statistical figure according to the instructions “Formatting an SPSS (statistical figure) for a Research Report.”
5. Use SPSS to calculate the appropriate measure of central tendency (i.e. mode, mean and/or median) for each variable. Only report the appropriate one for each variable. Explain your reasoning of why you chose the one you did in your report.
6. Obtain the standard deviation for each variable. Then, present the means and standard deviations in a sentence appropriate for inclusion in a research report. Finally, prepare a table showing the statistics.
7. Take all the information (1-6) and create a descriptive report showing all necessary tables and describing all data for each of the variables.
The research report should have a cover page and be in Times New Roman 12 font double spaced. The report should start with a short introduction (description) of your variables, where the data comes from, how it was measured/labeled etc.
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