Question

True or False:

-Before performing Regression, you should check that your data is normally distributed.

-If the data (and the residuals) are normally distributed, the residuals scatterplot will show the majority of residuals at the center of the plot for each value of the predicted score, with some residuals trailing off symmetrically from the center.

-You can test for linearity between an Independent Variable and the Dependent Variable by looking at a bivariate scatterplot.

-You can check homoscedasticity by looking at the residuals plot.

-Data are homoscedastic if the residuals plot is the same width for all values of the predicted Dependent Variable.

-High bivariate correlations are difficult to spot by just running correlations among Independent Variables.

-You can use transformations to correct for non-normal data, as well as heteroscedasiticy, nonlinearity, and outliers.

-Causal relationships among the variables cannot be determine through regression analysis.

Answer 1

1. Before performing Regression, you should check that your data is normally distributed - True

2. If the data (and the residuals) are normally distributed, the residuals scatterplot will show the majority of residuals at the center of the plot for each value of the predicted score, with some residuals trailing off symmetrically from the center - True

3. You can test for linearity between an Independent Variable and the Dependent Variable by looking at a bivariate scatterplot - True

4. You can check homoscedasticity by looking at the residuals plot - True

5.Data are homoscedastic if the residuals plot is the same width for all values of the predicted Dependent Variable -False

6. High bivariate correlations are difficult to spot by just running correlations among Independent Variables - False

7.You can use transformations to correct for non-normal data, as well as heteroscedasiticy, nonlinearity, and outliers - True

8. Causal relationships among the variables cannot be determine through regression analysis - False