Linear Regression Review

Front

What is Linear Regression?

Back

Linear Regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

Front

What does the slope in a linear regression equation represent?

Back

The slope indicates the rate of change of the dependent variable for each unit increase in the independent variable.

Front

What is the y-intercept in a linear regression equation?

Back

The y-intercept is the value of the dependent variable when the independent variable is zero.

Front

What does a strong negative correlation indicate?

Back

A strong negative correlation indicates that as one variable increases, the other variable tends to decrease.

Front

What does a strong positive correlation indicate?

Back

A strong positive correlation indicates that as one variable increases, the other variable also tends to increase.

Front

How do you interpret a correlation coefficient of -0.9?

Back

A correlation coefficient of -0.9 indicates a strong negative linear relationship between the two variables.

Front

How do you interpret a correlation coefficient of 0.8?

Back

A correlation coefficient of 0.8 indicates a strong positive linear relationship between the two variables.

Front

What is the purpose of the line of best fit?

Back

The line of best fit is used to summarize the relationship between variables in a scatter plot and to make predictions.

Front

What is the formula for a linear regression equation?

Back

The formula for a linear regression equation is y = mx + b, where m is the slope and b is the y-intercept.

Front

What does it mean if there is no correlation between two variables?

Back

No correlation means that there is no predictable relationship between the two variables; changes in one do not affect the other.