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Least-Squares Regression

Date post: 23-Jan-2016
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Least-Squares Regression. Correlation coefficient – r r describes the strength of the relationship In regression r 2 = fraction of variation in values of Y that is explained by X Example: The correlation between IQ and GPA was found to be a: r=0.50 b: r=0.99 - PowerPoint PPT Presentation
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Least-Squares Regression Correlation coefficient – r r describes the strength of the relationship In regression r 2 = fraction of variation in values of Y that is explained by X Example: The correlation between IQ and GPA was found to be • a: r=0.50 • b: r=0.99 What percent of the observed variation in the students’ GPAs can be explained by IQ alone?
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Page 1: Least-Squares Regression

Least-Squares RegressionCorrelation coefficient – r

r describes the strength of the relationship

In regression r2 = fraction of variation in values of Y that is explained by X

Example:The correlation between IQ and GPA was found to be

• a: r=0.50 • b: r=0.99

What percent of the observed variation in the students’ GPAs can be explained by IQ alone?

Page 2: Least-Squares Regression

Least-Squares Regression

What are the limits of r2?r2 indicates the strength of a relationship just like r

What is r2 when r = 1

What is r2 when r = -1

What is r2 when r = 0

1r1

Page 3: Least-Squares Regression

Least-Squares RegressionWhen developing a regression equation, it matters which is the explanatory and which is the response variable.

When calculating the equation we consider distances from the response variable to the line.

Reversing the roles will in turn produce different equations.

Page 4: Least-Squares Regression

ResidualsMeasure deviations from regression line

Vertical distances from the regression line

Residual =

Observed Predicted

yyo ˆ

Page 5: Least-Squares Regression

Residuals

Equation of relationship:Erosion = 1.461*Flow Rate + 0.04482

r = 0.943; r2 = 0.889For Flow Rate = 2.5 l/s:

What is the measured erosion rate?What is the predicted erosion rate?What is the residual?What does the sign of the residual tell you?

R = yyo ˆ

Page 6: Least-Squares Regression

ResidualsResidual Plots

Scatterplots of regression residuals against the explanatory variable.

Page 7: Least-Squares Regression

ResidualsIf regression line capture relationship between x and y, residuals should be random about the zero line.

Other residual plots….

Page 8: Least-Squares Regression

Residuals

Page 9: Least-Squares Regression

ResidualsCurved pattern – relationship not linear

Straight line is not the best description of the relationship

Increasing or decreasing spread about the zero line as x increases

Prediction of Y will be less accurate as x increases

Individual points with large residualsOutliers

Lie far from the line

Individual points extreme in x directionInfluential observations

Calculated residual not necessarily large

Page 10: Least-Squares Regression

Regression and Correlation

Correlation causation

What does a good correlation value mean?

When results from observational study are all we have, in the absence of other evidence, we cannot attribute the relationship to causality


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