Chapter 8 Regression Flashcards
Tells us the ration of explained vs unexplained variance
F
The b-value tells us the _______ of the line and the _________ of the ____________.If it is significant then _________ variable significantly predicts the_________ variable.
The b-value tells us the GRADIENT of the line and the STRENGTH of the RELATIONSHIP. IF it is significant then the …PREDICTOR variable significantly predicts the OUTCOME variable.
We use the _______________ ________ to check the correlation matrix for ________________.
We use the DESCRIPTIVES STATISTICS to check the correlation matrix for MULTICOLLINEARITY.
predictors that correlate TOO HIGHLY with one another are indicated by r values
great than .9
How do we assess the assumption of independent errors
Check Durbin Watson
Criteria for the Durbin Watson
close to 2 or at least between 1 and 3
When doing a hierarchical regression we assess the improvement of the model at each level by looking at the
change in R2 and whether it is significant
The individual contribution of variables to the regression model can be found in the…
For each predictor variable, you can see if it has made a significant contribution to predicting the outcome by looking at the ….
- Coefficients table
- column labelled Sig. (values less than .05 are significant).
what tells you the importance of each predictor in a regression model? What does a big value mean?
-standardized beta values
- bigger absolute value = more
important.
To check for multicollinearity, use the ____ _______ from the table labelled _________.
· If these values are less than ____, then there probably isn’t cause for concern.
- To check for multicollinearity, use the VIF VALUES from the table labelled COEFFICIENTS.
- If these values are less than 10, then there probably isn’t cause for concern.
If you have a VIF value greater than 10 but the average of all VIF values is not substantially greater than ___ there is probably no cause for concern.
1
A Cook’s distance greater than ___ indicates it could be influencing the model
1
List the things you check to determine if you have outliers or influential cases: - - - - -
Mahalanobis Distance Cooks Distance Average Leverage DfBeta Standardized Residuals
Mahalanobis Cooked an average sized beta and made a fairly standard gravy with the residue.
Which graph helps determine homogeneighty of variance? What do we want to see?
- ZPRED ZRESID
- random array of dots
what does it mean if the ZRESID ZPRED looks like a funnel
this is probably a
violation of the assumption of homogeneity of variance