Regression Analysis Quiz

What does a positive covariance between two variables indicate?

• Strong negative relationship

• Weak positive relationship

• Strong positive relationship

• No relationship

What assumption is violated if there is multicollinearity in a multiple regression model?

• Independence of residuals

• Homoscedasticity

• Normality of residuals

• Independence of predictors

In a multiple regression equation, what does each coefficient represent?

• The mean of the dependent variable

• The slope of the regression line

• The intercept of the regression line

• The effect of an independent variable, holding other variables constant

What is the method used to find the "best fit" line in regression analysis?

• Least Squares

• Maximum Likelihood

• Gradient Descent

• Chi-square

What is the main goal of regression analysis?

• To find the correlation coefficient

• To make predictions about the dependent variable based on the independent variable(s)

• To create scatter plots

• To calculate covariance

Which visualization is commonly used to display the relationship between two continuous variables?

• Histogram

• Box Plot

• Scatter Plot

• Cross Table

In the context of regression analysis, what does "regression to the mean" imply?

• Extreme values in one variable tend to be associated with less extreme values in the other variable.

• Extreme values in one variable tend to be associated with more extreme values in the other variable.

• The regression line is a perfect fit to the data.

• There is a non-linear relationship between the variables.

What does the Standard Error of Estimate (SEE) measure in regression analysis?

• The average error between predicted and observed values

• The variance of the residuals

• The slope of the regression line

• The correlation coefficient

In polynomial regression, what degree best fits a linear relationship?

• 1st degree

• 2nd degree

• 3rd degree

• 0th degree

What does the Adjusted R-squared account for in multiple regression?

• The number of independent variables

• The mean absolute error

• The degree of the polynomial

• The sample size