Assignment 1 – Testing for Multiple Regression

The SPSS assignment that will be submitted on day 7 of week 10 has two parts.

In Part 1, you will run a multiple regression with 3 interval-ratio (scale) variables.

In Part 2 you will run a multiple regression with 2 scale variables and one dummy-coded variable and report on the assumptions of multiple regression.

For both analyses, use either the Afrobarometer data set or the HSLS data set. Use the same data set for Part 1 and Part 2.

Below I discuss each part in more detail.

Part 1:Multiple Regression with Scale Variables
Run a multiple regression with two scale IVs and one scale DV.

IVs = select two IVs that both show as scale in the selected data set.
DV = select one DV that is scale data

Here is an overview of how to run the Multiple Regression

Analyze > Regression > Linear

Enter your 1 (and only 1) DV into the Dependent box.
Enter your 2 (and only 2) IVs into the Independent(s) box.

Click OK

NOTES:
– all three variables should be interval or ratio variables. They should be listed as scale variables in your data set
– the variable you wish to predict should be entered as the IV
– leave the Method as “Enter”, this is referred to as a standard regression and it enters all of the IVs at the same time, whether or not they are significantly related to the DV
– select Only 2 IVs for the discussion and assignments for multiple regression.

You should address all of the following:
– State your research question
– State your null hypothesis
– Describe your outcome variable (DV) and how it was measured.
– Describe the predictor variables (IVs) and how they were measured. (Select 2 and only 2 IVs)
– clearly identify the name and label of the variables as they appear in the data set; identify the data set
– Indicate whether the overall model was significant or not, explain how you know
– indicate whether each of your two predictors were significant or not, explain how you know
– report the results of your multiple regression analysis in APA format, interpret the effect size usingRsquare (see pp. 440 – 441, and p. 450 in your text and my example below)
– ensure you clearly explain whether the variables are significant predictors or not and what the regression equation is for your results.
– Discuss implications for positive social change
– include your output at the end of the paper in a separate Appendix for Part 1
–do not use sei10, educ, and prestg10 as your variables!

Part 2: Multiple Regression with Dummy Coding
a) Run a multiple regression with one dummy coded IV, one scale IV, and one scale DV.
b) Report on the assumptions, run diagnostics to test whether they are met, report on the implications for your model.

First, select your variables.

IV₁= nominal variable that can be coded into two categories one having the property and the other not having the property. Istronglyencourage you to select a nominal variable with only two response options.

IV₂= an interval or ratio variable, shown as scale data in SPSS

DV = an interval or ratio variable, shown as scale data in SPSS

Second, dummy code your IV₁

Third, run the multiple regression with the additional diagnostics for testing assumptions of the test.