Data Analysis with R by Tony Fischetti

Author:Tony Fischetti [Fischetti, Tony]
Language: eng
Format: epub
Publisher: Packt Publishing
Published: 2015-12-21T23:00:00+00:00

Consequently, the equations describing our predictive model are:

Meaning that the is the mean of weight lost in the control group, is the difference in the weight lost between control and diet only group, and is the difference in the weight lost between the control and the diet and exercise group.

> # the dataset is in the car package > library(car) > model <- lm(wl2 ~ factor(group), data=WeightLoss) > summary(model) Call: lm(formula = wl2 ~ factor(group), data = WeightLoss) Residuals: Min 1Q Median 3Q Max -2.100 -1.054 -0.100 0.900 2.900 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.3333 0.3756 8.874 5.12e-10 *** factor(group)Diet 0.5833 0.5312 1.098 0.281 factor(group)DietEx 2.7667 0.5571 4.966 2.37e-05 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 1.301 on 31 degrees of freedom Multiple R-squared: 0.4632, Adjusted R-squared: 0.4285 F-statistic: 13.37 on 2 and 31 DF, p-value: 6.494e-05

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