Indicate the correct option(s) for each question. There can be more than one correct option per question.

1.The Pearson correlation coefficient:

A.can be used when both qualitative variables are normally distributed.

B.is not affected by outliers.

C.expresses a linear relationship between 2 qualitative variables.

D.can be used when both variables are on the ratio measurement scale.

2.The Spearman correlation coefficient:

A.can be used when 2 variables are on nominal measurement scale.

B.is not affected by outliers.

C.expresses a strictly monotonic relationship between 2 quantitative variables.

D.can be used when one variable is normally distributed and one is not.

3.Which of the following statement on Chi-Square Test is correct?

A.It assesses whether a linear relationship exists between 2 quantitativevariables.

B.It assesses whether a linear relationship exists between 2 qualitative variables.

C.Can be used to ascertain if there is an association between a nominal variable and an ordinal variable.

D.Can be used to assess the strength of correlation between 2 quantitativevariables.

4.Linear regression can be used for:

A. building a relationship between a categorical dependent variable and 1 or more continuous independent variables.

B.building a relationship between a continuous dependent variable and 1 or more continuous independent variables.

C.building a relationship between a continuous dependent variable and 1 or more continuous or categorical independent variables.

D. building a relationship between a continuous dependent variable and 1 or more categorical independent variables.

5.Multi-collinearity means that there is:

A.collinearity among the dependent variable and the independent variables.

B.inter-correlation among the dependent variable and the independent variables

C.collinearity among the independent variables.

D.strong correlation among the dependent and the independent variables.

6.Which of the following statement(s) on R² of a linear regression model is/are correct?

A. R²is the variance in the dependent variable that is explained jointly by the independent variables after taking into account the chance contribution by some independent variables.

B.R²is called the multiple correlation and it is the sum of all the correlation coefficients of the independent variables with the dependent variable.

C.R²is the percent of variance in the dependent variable that is explained by the independent variable which has the highest impact on the dependent variable.

D. R²is the percent of variance in the dependent variable that is explained jointly by the independent variables.

7.The Standardized Coefficient (Beta) in a linear regression model can be used:

A.to assess whether there is a significant difference in the means/medians among the independent variables.

B. to assess the impact of independent variables on each other.

C. to assess which independent variable has the highest impact on the dependent variable.

D. to judge the relative predictor power of the independent variables on the dependent variable.

8.The Tolerance is a measure which:

A. has the same interpretation as Adjusted R².

B.serves the same purpose as the Variance-Inflation Factor, that is to assess multi-collinearity among the independent variables.

C can be used to gauge whether a linear relationship exists among the independent variables.

D. can be used to gauge whether a linear relationship exists between the dependent variable and the independent variables.