Linear Regression and Residuals - Using Desmos

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.

Tags

CCSS.8.SP.A.2

Front

What is the equation of a linear regression model?

Back

Tags

CCSS.8.EE.B.5

Front

What does the slope in a linear regression equation represent?

Back

The slope (m) represents the change in the dependent variable (y) for a one-unit change in the independent variable (x).

Front

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

Back

The y-intercept (b) is the value of the dependent variable (y) when the independent variable (x) is zero.

Tags

CCSS.HSF.LE.B.5

Front

What is a residual in the context of linear regression?

Back

Tags

CCSS.HSS.ID.B.6B

Front

How do you calculate a residual?

Back

Front

What is the purpose of using Desmos for linear regression?

Back

Desmos is an online graphing calculator that allows users to visualize data, create linear regression models, and analyze relationships between variables.

Front

What is the correlation coefficient (r)?

Back

The correlation coefficient (r) measures the strength and direction of a linear relationship between two variables, ranging from -1 to 1.

Tags

CCSS.HSS.ID.C.8

Front

What does a correlation coefficient of 0.9998 indicate?

Back

A correlation coefficient of 0.9998 indicates a very strong positive linear relationship between the two variables.

Front

How do you interpret a positive residual?

Back

A positive residual indicates that the observed value is greater than the predicted value, suggesting that the model underestimates the actual data point.

Tags

CCSS.HSS.ID.B.6B