r:linear_regression
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r:linear_regression [2018/12/07 08:16] – [Multiple Regression] hkimscil | r:linear_regression [2019/06/13 10:15] (current) – hkimscil | ||
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====== Multiple Regression ====== | ====== Multiple Regression ====== | ||
+ | regression output table | ||
| anova(m) | | anova(m) | ||
| coefficients(m) = coef(m) | | coefficients(m) = coef(m) | ||
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* What is R< | * What is R< | ||
* How many cars are involved in this test? (cf. df = 90) | * How many cars are involved in this test? (cf. df = 90) | ||
+ | * df + # of variables involved (3) = 93 | ||
+ | * check ' | ||
* If I eliminate the R< | * If I eliminate the R< | ||
+ | </ | ||
+ | <WRAP box info>The last question: | ||
+ | * If I eliminate the R< | ||
+ | * to answer the question, use the regression output table: | ||
+ | |||
+ | R< | ||
+ | = | ||
+ | |||
+ | < | ||
+ | Analysis of Variance Table | ||
+ | |||
+ | Response: Cars93$MPG.city | ||
+ | Df Sum Sq Mean Sq F value Pr(> | ||
+ | Cars93$EngineSize | ||
+ | Cars93$Price | ||
+ | Residuals | ||
+ | --- | ||
+ | Signif. codes: | ||
+ | |||
+ | > sstotal = 1465+131+1310 | ||
+ | > ssreg <- 1465+131 | ||
+ | > ssreg/ | ||
+ | [1] 0.54921 | ||
+ | > | ||
+ | > # or | ||
+ | > 1-(deviance(lm.model)/ | ||
+ | [1] 0.54932 | ||
+ | </ | ||
+ | |||
+ | |||
</ | </ | ||
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* $\hat{Y} = \widehat{\text{MPG.city}}$ | * $\hat{Y} = \widehat{\text{MPG.city}}$ | ||
- | <WRAP box help>in the meantime, | + | <WRAP box info>in the meantime, |
< | < | ||
Cars93$EngineSize | Cars93$EngineSize | ||
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> | > | ||
</ | </ | ||
+ | Beta coefficients are not equal to correlations among variables. | ||
</ | </ | ||
r/linear_regression.1544138172.txt.gz · Last modified: 2018/12/07 08:16 by hkimscil