Bellwork: December 16: Review Linear Regression and Correlation

• The point where the line crosses the x-axis

• The intercept of the regression line

Tags

CCSS.HSF.LE.B.5

• The slope of the regression line

• The y-intercept of the line

• The residual value

Tags

CCSS.HSF.LE.B.5

What is the primary purpose of linear regression?

• To find the mean of the data set

• To predict the value of a dependent variable based on an independent variable

• To test for causation between two variables

• To calculate the median of the data

What is a residual in linear regression?

• The slope of the regression line

• The value of the independent variable

What does a residual plot with a random scatter of points indicate?

• A non-linear relationship between variables

• That the regression model is appropriate for the data

• A strong positive correlation

• Multicollinearity

• To measure the strength and direction of the relationship

• To determine how well the regression line fits the data

• To calculate the slope of the regression line

• To test for independence between variables

Which of the following indicates a perfect fit of the regression model?

Which method is commonly used to find the line of best fit in linear regression?

• Maximum Likelihood Estimation

• Least Squares Method

• Bootstrap Method

• Principal Component Analysis

In multiple linear regression, what issue arises when independent variables are highly correlated?

• Heteroscedasticity

• Multicollinearity

• Non-linearity

• Overfitting

What assumption is NOT required for linear regression?

• Linearity of the relationship between variables

• Normally distributed residuals

• Homoscedasticity (constant variance of residuals)

• Equal number of independent and dependent variables