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What is a linear regression model?

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A linear regression model is a statistical method used to model the relationship between a dependent variable (y) and one or more independent variables (x) by fitting a linear equation to observed data.

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CCSS.8.SP.A.2

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What does a positive correlation coefficient indicate?

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A positive correlation coefficient indicates that as one variable increases, the other variable also tends to increase, showing a positive linear relationship.

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CCSS.HSS.ID.B.5

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What does a negative correlation coefficient indicate?

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A negative correlation coefficient indicates that as one variable increases, the other variable tends to decrease, showing a negative linear relationship.

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CCSS.HSS.ID.B.5

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What is the formula for a linear function?

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CCSS.8.F.B.4

CCSS.HSF.LE.A.2

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What does the slope of a linear function represent?

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The slope of a linear function represents the rate of change of the dependent variable (y) with respect to the independent variable (x).

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CCSS.8.EE.B.5

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What is a residual in the context of linear regression?

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A residual is the difference between the observed value and the predicted value of the dependent variable in a regression model.

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What does it mean if two linear functions have no points of intersection?

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If two linear functions have no points of intersection, it means they are parallel lines and have the same slope but different y-intercepts.

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CCSS.8.EE.C.8B

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How do you determine if a linear model is a good fit for data?

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A linear model is a good fit for data if the residuals are randomly distributed and there is a strong correlation between the independent and dependent variables.

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What is the significance of the y-intercept in a linear equation?

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CCSS.HSF-IF.C.7A

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What is the difference between a strong and weak correlation?

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A strong correlation means that the data points are closely clustered around the line of best fit, while a weak correlation indicates that the data points are more spread out.

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CCSS.HSS.ID.B.5