1. Which of the following cannot be achieved by using multivariate methods?

1. relationships between variables are specific to a single context
2. assessing whether relationships between study variables vary depending on the level of other variables
3. proving causal relationships between variables
4. assessing influences of predictor variables which vary from one dependent variable to another

2. What is a latent variable?

1. a variable which cannot be measured directly
2. a variable whose impact is hidden
3. a variable which is left out of a causal model
4. a predictor variable which is not significant

3. Which of the following is NOT required for a multiple regression model?

1. more than one predictor variable
2. a category dependent variable
3. a set of observed variables
4. a predicted causal model about relationships among variables

4. The relative importance of a predictor variable in regression analysis is shown by ______.

1. a product-moment correlation coefficient
2. a multiple R coefficient
3. a regression coefficient
4. a factor loading

5. In hierarchical regression analysis, ______.

1. the researcher chooses the ordering of predictor variables to be entered based on theory
2. the order of entering predictor variables depends on the size of their correlations with the dependent variable
3. the order of entering variables is determined by how well each one adds to predicting the dependent variable
4. the most important variable is entered first

6. What is the difference between ANOVA and MANOVA models?

1. MANOVA models have more than one category predictor variable.
2. MANOVA models have more than one dependent variable.
3. MANOVA models always include covariates.
4. MANOVA models are for multiple groups and ANOVA models are for one group.

7. What is the difference between multiple regression analysis and logistic regression analysis?

1. Logistic regression analysis includes a category dependent variable.
2. Multiple regression analysis includes more than one dependent variable.
3. Logistic regression models always contain covariates.
4. Multiple regression analysis allows predictors to be added sequentially.

8. Which of the following is NOT required in a structural equation model?

1. a statement about which relevant variables to include
2. a hypothesis about cause–effect relationships among variables
3. fixed and free parameters
4. both latent variables and observed variables

9. In the context of SEMs, what is an identified model?

1. a model which fits the assumptions of the method
2. a model with enough information to obtain unique estimates of the components of a hypothesised model
3. a model which confirms the researcher’s hypotheses
4. a model which is the simplest possible

10. What is goodness of fit?

1. how well a model fits the researcher’s expectations
2. how well the predictions from a model are consistent with empirical data
3. the significance level from a statistical test
4. how well empirical data conform to the technical assumptions of a statistical method