Linear Regression Analysis Quiz

What is a fundamental requirement for a linear regression model?

• Linear relationship between variables

• Heteroscedasticity in residuals

• Nonlinear relationship between variables

• Multicollinearity among variables

Which test is NOT typically used to check for normal distribution of errors in small samples?

• QQ plot

• Kolmogorov-Smirnov test

• Shapiro-Wilk test

• Histogram analysis

What is the purpose of using a QQ plot in regression analysis?

• To determine the homoscedasticity of residuals

• To evaluate the normality of error distribution

• To assess the linearity of the model

• To check for multicollinearity

What does homoscedasticity imply in a linear regression model?

• Constant variance of residuals

• No variance in residuals

• Increasing variance of residuals

• Decreasing variance of residuals

What is multicollinearity?

• A condition where dependent variables are correlated

• A condition where independent variables are correlated

• A condition where residuals are normally distributed

• A condition where the regression line is nonlinear

How can multicollinearity be diagnosed?

• By using a histogram

• By plotting a QQ plot

• By calculating the variance inflation factor

• By checking the linearity of the regression line

What does a variance inflation factor greater than 10 indicate?

• Presence of multicollinearity

• Absence of multicollinearity

• Absence of normal distribution

• Presence of homoscedasticity

What is the role of tolerance in diagnosing multicollinearity?

• It measures the linearity of the model

• It indicates the normality of errors

• It shows the degree of multicollinearity

• It assesses the variance inflation factor

Which online tool feature allows you to check linear regression assumptions?

• Data cleaning

• Statistics calculator

• Data visualization

• Regression line plotting

What is the significance of checking conditions in a regression analysis tool?

• To visualize the regression line

• To ensure data is normally distributed

• To verify the accuracy of predictions

• To confirm the assumptions of the regression model