OLS_Assumptions08B part 2

OLS_Assumptions08B part 2 - Assumptions of Ordinary Least...

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1 Assumptions of Ordinary Least Squares Regression (Part 2) ESM 206 Jan 21, 2008

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2 7. Errors not normally distributed Problem: Parameter estimates are unbiased P-values are unreliable Regression fits the mean; with skewed residuals the mean is not a good measure of central tendency Diagnosis: examine QQ plot of residuals
3 -2 -1 0 1 2 -20 -10 0 10 20 30 40 norm quantiles Chlorophyll\$residuals.LinearModel.1 1. Save residuals to dataset using Models -> Add Observation Statistics to Data 2. Make a QQ plot

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4 Errors not normally distributed Problem: Parameter estimates are unbiased P-values are unreliable Regression fits the mean; with skewed residuals the mean is not a good measure of central tendency Diagnosis: examine QQ plot of Studentized residuals Corrects for bias in estimates of residual variance -2 -1 0 1 2 -2 -1 0 1 2 3 norm quantiles Chlorophyll\$rstudent.LinearModel.1
5 1. Models -> Graphs -> Residual Quantile-Comparison Plot -2 -1 0 1 2 -2 -1 0 1 2 3 t Quantiles Studentized Residuals(LinearModel.1)

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6 Errors not normally distributed Problem: Parameter estimates are unbiased P-values are unreliable Regression fits the mean; with skewed residuals the mean is not a good measure of central tendency
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This note was uploaded on 08/06/2008 for the course ESM 206 taught by Professor Kendall,berkley during the Spring '08 term at UCSB.

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OLS_Assumptions08B part 2 - Assumptions of Ordinary Least...

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