Due Date: Wednesday, May 18th. Beginning of Class
Partisanship |
Religion Not Important |
Religion Important |
Total |
Democrat |
130 |
220 |
350 |
Independent |
85 |
255 |
340 |
Republican |
35 |
275 |
310 |
Total |
250 |
750 |
1000 |
Part B. Initial Test for Your Data Project
#2. You are going to begin to explore the relationships between one of the independent variables in your hypothesis and your dependent variable, but we’ll wait until the final homework to ask you to conduct tests of statistical significance.
Restate the hypothesis that you proposed in the first homework. Then state the null hypothesis.
Using only one of your independent variables, use SPSS to produce a graph of the bivariate relationship between this independent variable and your dependent variable. If the independent variable is an interval or ratio variable, you can produce a scatterplot (Click on the “Graphs” pulldown menu, then select “Scatter,” and then “Define.” Pull one independent variable into the x-axis box, and then pull your dependent variable into the y-axis box). If the independent variable is a nominal or ordinal variable, you can produce a bar chart that reports proportions or mean or median values of the dependent variable for cases that take on different levels of the independent variable (just like with ethnicity and turnout in class). Print out the graph, and describe the relationship that you see. Do they appear to be correlated? Is the correlation negative or positive?
Think of a possible confounding variable or an intervening variable that is included in the dataset that you are using (i.e. make sure it appears in the list of variables for that dataset in the SPSS manual). Later, you will explore whether it really is a confound or an intervening variable, but for now just make an argument that it might fit the definition of one of these sorts of variables, going through all three criteria for a confound or explaining why it is an intervening variable.
Below are the new SPSS hints:
If you have a nominal or ordinal independent variable:
While you are viewing the dataset, go up to the “Graphs” pull down menu, then select “Legacy Dialogs,” then select “Bar,” and double click on “Simple.” When the dialog box opens up, pick your independent variable from the list of variables on the left, and place it into the “Category Axis” box. Then go to “Bars Represent,” and click the button for “Other Statistic (e.g., mean), and put in your dependent variable. Click “OK” at the bottom, and you will have a bar graph where each bar is the mean value that your dependent variable takes on for a given value of the independent variable.
If you have an interval or ratio independent variable:
While you are viewing the dataset, go up to the “Graphs” pull down menu, then select “Legacy Dialogs,” then select “Scatter/Dot,” click on “Simple Scatter,” then select “Define.” When the dialog box opens up, pick your independent variable from the list of variables on the left, and place it into the “X Axis” box, and put your dependent variable into the “Y Axis” box. Then click “OK.”
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