_____ are underlying constructs that are not directly observable and cannot be measured by one single thing.

• Observable variables

• Factor variables

• Latent variables

• Multi variables

Which of the following statements is NOT true regarding confirmatory factor analysis (CFA)?

• CFA requires you to predetermine the number of factors.

• CFA is best used in situation where you have no expectations of what the outcome of your analysis would be.

• CFA requires you to predetermine which observable variables are related to each factor.

• CFA requires you to predetermine a specific hypothesis.

Which of the following statements regarding exploratory factor analysis (EFA) is NOT correct?

• EFA involves a specific hypothesis based on previous research or theory.

• EFA identifies the factor structure.

• EFA can explain a maximum variance amount.

• EFA does not require you to predetermine the number of factors or the relationship between the factors and the observed variables.

Which of the following is NOT one of the primary goals of factor analysis?

• Determine how many factors underlie a set of observable variables.

• Provide a method of explaining variance among observable variables by using fewer, newly created factors.

• Define the meaning or content of the observable variables.

• Reduce data by allowing us to extract a small set of factors from a larger set of observable variables.

What is factor analysis?

• A statistical method that is used to determine whether a group of observable variables are related to a smaller group of underlying factors.

• A statistical method used to calculate the correlations between underlying factors.

• A statistical method used to determine whether there are differences between observable variables.

• None of these answers are correct.

T/F: Chi-Square looks to see if two categorical variables are related.

• True

• False

T/F: Sampling error is any error that is due to variance in your sampled group of people.

• False

• True

T/F: Type 2 error is the possibility of rejecting the null hypothesis when the null is actually true.

• False

• True

T/F: Type 1 error is the possibility of rejecting the null hypothesis when the null is actually true.

• True

• False

T/F: Type 2 error is the possibility of failing to reject the null hypothesis.

• True

• False