Statistics Regression & Correlation Analysis 3

Question 1

What is logistic regression used for?

Accepted Answer

Predicting a binary or categorical outcome variable

Answer

Predicting a continuous outcome variable

Answer

Comparing means of two groups

Answer

Testing the normality of a distribution

Question 2

What does the adjusted R² penalize for compared to R²?

Accepted Answer

Adding predictors that don't improve the model

Answer

Having a small sample size

Answer

Using non-normal predictors

Answer

Having correlated residuals

Question 3

Which regression diagnostic plot is used to check the linearity and homoscedasticity assumptions?

Accepted Answer

Residuals vs. fitted values plot

Answer

Normal Q-Q plot

Answer

Histogram of the response variable

Answer

Scatter plot of predictors

Question 4

What is the purpose of polynomial regression?

Accepted Answer

To model a curved (non-linear) relationship between X and Y

Answer

To compare means across multiple groups

Answer

To reduce the number of predictor variables

Answer

To test for multicollinearity

Question 5

In the context of regression, what is overfitting?

Accepted Answer

A model that fits the training data too closely and performs poorly on new data

Answer

A model with too few predictors to explain the outcome

Answer

A model where all coefficients are statistically significant

Answer

A model that underestimates the true population effect

Question 6

What does the standard error of the estimate (SEE) measure in regression?

Accepted Answer

The typical size of the prediction error (residual)

Answer

The standard deviation of the slope coefficient

Answer

The correlation between observed and predicted values

Answer

The variance of the predictor variable