1) Download the 2018 GSS data. For the rest of this assignment you will work with this dataset that I downloaded. The data set is named “Soc 108 Assignment 5 GSS2018 Data File.dta” and is on GauchoSpace.
Open the data set and then run the “describe” command to see what variables are in the data. Put an image of part of the output from the “describe” command here:
What are ten variables you would be interested in further analyzing? Write the ten variable names here (list of ten variable names).
2) Write a hypothesis about the relationship between two variables in the 2018 GSS dataset that I provided for you (see Carr et al. 2018: 55) (1 sentence). These can be the same variables you used in Assignment 5, or you can pick new variables.
Research the variables in the https://gssdataexplorer.norc.org before you finalize your hypothesis. The DV must be a—more or less—continuous variable OR an ordinal categorical variable (Carr et al. 2018: 114). The IV must be a—more or less—continuous variable OR a binary, categorical variable (Carr et al. 2018: 114).
Make sure when you write up the hypothesis, both the GSS name of the variable and the “plain English” name of the variables are in the hypothesis. That is, I want it to be clear what the concept you are testing is, as well as what the exact variables you will use to test it are.
3) Create a path diagram representing the relationship between the two variables (Carr et al. 2018: 505-517). Paste the image of the path diagram here. Describe, in words, the relationship represented by the path diagram (1-5 sentences).
4) Which variable is the IV and which is the DV? (1 sentence)
5) What is your null hypothesis (Carr et al. 2018: 55; 498)? (1 sentence)
6) Look up each of the two variables here: https://gssdataexplorer.norc.org/. Write 2-3 paragraphs describing something you learned about the variables from looking at the GSS Data Explorer.
7) Run the following commands for each variable and use the snip tool to copy and paste the output for each of the two variables below (for a total of 6 separate images). Take some time to look at the output and think about what it means:
a. Codebook
b. Describe
c. Tabulate
8) Interpret some of the output from running these six commands. Write 2-3 paragraphs here describing what you learned about the variables from looking at the Stata output.
9) Run a regression using these two variables. Use the “reg” command.
The DV must be a—more or less—continuous variable OR an ordinal categorical variable (Carr et al. 2018: 114). The IV must be a—more or less—continuous variable OR a binary, categorical variable (Carr et al. 2018: 114).
In the “reg” command in Stata, the DV goes first.
Paste an image of the regression output here (1 image).
10) Create a scatter plot AND regression line in the same figure for your two variables. Use the snip tool to copy and paste the figure output here. The command for generating this output is “graph twoway lfit.”
11) Discuss what the regression coefficient associated with your IV tells you about the relationship between your two variables. (1-2 paragraphs)
12) What is your p-value associated with your regression coefficient (associated with your IV)? Is it statistically significant at the conventional level of .05? (1-2 sentences)
13) Describe, in words, the meaning of the p-value associated with your regression coefficient. (1-2 sentences)
14) Were you able to reject the null hypothesis? (1-2 sentences)
15) Did you find support for your hypothesis? Elaborate. (1-3 paragraphs)
16) Next, you will add a third “control” (Carr et al. 2017: 509-512) variable to your model and write a hypothesis that predicts the relationship among these three variables.
First, identify a variable that you think might be a good control variable to add to your model. Research the new variables in the https://gssdataexplorer.norc.org before you finalize your hypothesis. Add this third variable to your hypothesis and write this new hypothesis.
Make sure when you write up the hypothesis, both the GSS name of the variable and the “plain English” name of the variables are in the hypothesis. That is, I want it to be clear what the concept you are testing is, as well as what the exact variables you will use to test it are.
The DV must be a, more or less, continuous variable OR an ordinal categorical variable (Carr et al. 2018: 114). The IV and the control variable should be a, more or less, continuous variable OR a binary, categorical variable (Carr et al. 2018: 114). (1-2 sentences)
17) Create a path diagram representing the relationship between the three variables (Carr et al. 2018: 505-517). Paste the image of the path diagram here. Describe, in words, the relationship represented by the path diagram (1-5 sentences).
18) Which variable is the IV, DV, and which is the control variable? (1-2 sentences)
19) Next, look up the “control” variable here: https://gssdataexplorer.norc.org/. Write 1-2 paragraphs describing something you learned about the variable from looking at the GSS Data Explorer.
20) Run the following commands for the control variable and use the snip tool to copy and paste the output below (for a total of 3 separate images). Also take some time to look at the output and think about what it means:
d. Codebook
e. Describe
f. Tabulate
21) Interpret the output. Write 1-2 paragraphs here describing something you learned about the control variable from looking at the Stata output.
22) Run a regression using these three variables.
The DV must be a—more or less—continuous variable OR an ordinal categorical variable (Carr et al. 2018: 114). The IV and the control variables must be—more or less—continuous variables OR binary, categorical variables (Carr et al. 2018: 114).
In the “reg” command in Stata, the DV goes first, the IV goes second and the control variable goes third.
Use the snip tool to copy and paste the regression output here.
23) Discuss what the regression coefficient associated with your IV tells you about the relationship between your three variables. Discuss how the regression coefficient associated with the IV changed when you added a control variable. (1-3 paragraphs)
24) What is the p-value associated with your IV regression coefficient? Is it statistically significant at the conventional level of .05? (1-2 sentences)
25) Describe, in words, the meaning of the p-value associated with your IV regression coefficient. (1-2 sentences)
26) Discuss what the regression coefficient associated with your control variable tells you about the relationship between your three variables. (1-2 paragraphs)
27) What is your p-value associated with your control variable coefficient? Is it statistically significant at the conventional level of .05? (1-2 sentences)
28) Describe, in words, the meaning of the p-value associated with your control variable coefficient. (1-2 sentences)
29) Did you find support for your hypothesis identified in question 16, above? Elaborate. (2-3 paragraphs)
