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 represents the change in the dependent variable for a one-unit change in the independent variable.

Front

What is the formula for a simple linear regression equation?

Back

The formula is y = mx + b, where m is the slope and b is the y-intercept.

Front

What does a positive correlation indicate in linear regression?

Back

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

Front

What does a negative correlation indicate in linear regression?

Back

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

Front

What is the purpose of calculating the linear regression equation?

Back

The purpose is to predict the value of the dependent variable based on the values of the independent variable(s).

Front

What is the significance of 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

How can you interpret a weak negative correlation?

Back

A weak negative correlation suggests that there is a slight tendency for one variable to decrease as the other variable increases, but the relationship is not strong.

Front

What is the role of residuals in linear regression?

Back

Residuals are the differences between observed values and the values predicted by the regression model; they help assess the model's accuracy.

Front

What does it mean if the linear regression model has a high R-squared value?

Back

A high R-squared value indicates that a large proportion of the variance in the dependent variable is explained by the independent variable(s).