Chartered Financial Analyst (CFA) Practice Exam Level 2

The F Test in regression analysis evaluates the overall significance of the regression model. It assesses whether at least one of the independent variables in the model has a statistically significant relationship with the dependent variable. Essentially, the F Test examines if the explained variance in the dependent variable is significantly greater than the unexplained variance. If the F statistic is significantly larger than 1, it suggests that the model has a good fit and that the independent variables as a whole are meaningful in explaining the variation in the dependent variable. This is crucial in determining if the regression model is useful and warrants further analysis of the individual predictors.

The other options pertain to different aspects of regression analysis: individual predictors are assessed using t-tests, multicollinearity is examined through variance inflation factors, and the variance of the dependent variable pertains to descriptive statistics rather than the overall significance of the regression model.