Reading the Regression Analysis
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Lets look at one more sample data and try to read the Regression Analysis Summary. Refer Here for the dataset
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The Summary which we got is as shown below
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What we really want?
- Regression equation:
y-hat = 528.06717 + 14.833x
- Significance
- Explanatory power
- Regression equation:
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Regression Statistics
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ANOVA:
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Multiple R: This is absolute value of teh correlation coeffecient of two variables (X and Y)
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Standard error: This is measure of precision of the model
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R-squared = measures how much of total variability is explained by your model
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Adjusted R-squared is the modified version of R-squared that has been adjust for number of predictors in the model
- Multivariate Regressions are always better than univariate, as with each additonal value you add the explanatory power may increase or stay the same
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F-Statistic: This tests the overall significance of the model
- H0 :
b1 = b2 = b3...bk=0
- H1: at least one of b(i) !=0
- H0 :
Multiple Linear Regression model
- So far in Single linear regression
- So in multiple linear regression