1. Multiple Regression What is our research question?  How does IV1, IV2, IV3 influence the DV What unique contribution to variation in the DV does IV1 make when holding IV2 & IV3 constant? What unique contribution to the DV does IV2 make when holding IV1 & IV3 constant?

2. Example: TVhours regressed onto Educ, Age, Income Hr1: As education increases TV viewing decreases. Hr2: As income increases TV viewing decreases. Hr3: As age increases TV viewing increases.

3. Unique & Shared Variation

4. Output Important Statistics: R-squared = The amount of variation explained by all of the IVs taken together. AVOVA Box F Test=Tells us if the regression model is a good fit for this data. T-Test= Significance test for each Beta.

5. How to read B & Beta: B is the unstandardized beta.  Tells us the amount of change in the DV for a one unite change an IV, holding all other IVs constant. Beta is the standardized beta.  Tells us about the strength of an IV on the DV holding all other IVs constant.  The largest Beta has the strongest impact on the IV. Beta can range from -1 to +1 with 0 indicating no relationship.

6. SPSS Output See overhead