Multiple Regression

Which parameter estimate is the location parameter?

• slope

• intercept

• standardized beta

• interaction term

Tags

CCSS.8.SP.A.2

When will you use hierarchical entry regression? When

• you have less than 10 predictors

• predictors are based on theory

• I want to consider only significant predictors

• I want to appear statistically cool

The partial F-test

• is an omnibus test

• considers the reduction in error when moving from the complete model to the reduced model

• considers the reduction in error when moving from the reduced model to the complete model

• can only be conceptualized as a reduction in error

How much additional variability in Y is explained by the complete model over the reduced model?

• .665

• .335

• .578

• .330

Tags

CCSS.HSS.ID.B.6B

What F distribution did SPSS select to evaluate the probability of the Partial F for the Complete Model

• An F with 198 degrees of freedom

• SPSS did not select an F distribution, it selected a Partial F distribution

• I don't have enough information to answer this question

• An F distribution with 2 and 196 degrees of freedom

Tags

CCSS.HSS.ID.B.6A

If one additional predictor was added when moving from the reduced to the complete model what is the semi-partial correlation of that predictor and Y?

• I need the Coefficients table to answer this question

• .330

• .574

• .1089

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

When you have categorical predictors, the intercept is the

• average difference between all groups

• difference between the group of interest and the reference group

• mean of the reference group

• value of the basic mean model

An interaction

• is a second-order term

• causes the linear model to convert to a plane

• must have crossing contour lines

• is mediation

Tags

CCSS.HSS.ID.B.6B

When an interaction is significant, what is the researcher's next step? Evaluate

• the significance of each predictor (i.e., evaluate the main effects)

• the conditional slopes at a fixed level of the independent variable(s)

• the degree to which one independent variable impacted the others

• whether it introduced multicollinearity into the model

Tags

CCSS.HSS.ID.B.6B

Matrix algebra is important because

• its super fun and makes us look mathematically cool

• helps us to understand what the computer is actually doing

• is efficient

• all of the above

Tags

CCSS.HSN.VM.C.6

CCSS.HSN.VM.C.8

CCSS.HSN.VM.C.9