Question

Need R codes to compile and plots , no hand written.

Step-1: Type the data in R

Step-2: Perform Least-Squares regression

Step-3: Make a normal Probability Plot using rstudent residuals

Step-4: Plotting residuals versus predicted response yhat

Step-5: Plotting Residuals versus each regressor.

Step-6: Partial regression plots of residuals vs. regressors

Step-7: Partial regression plots of residuals vs. regressors

data:  (p.555 y, x1 and x5).

y <- c(271.8, 264,238.8,230.7,251.6,257.9,263.9,266.5,229.1,239.3,258,
257.6,267.3,267,259.6,240.4,227.2,196,278.7,272.3,267.4,254.5,224.7,
181.5,227.5,253.6,263,265.8,263.8)

x1 <- c(783.35, 748.45,684.45,827.8,860.45,875.15,909.45,905.55,756,769.35,793.5,801.65,819.65,808.55,774.95,711.85,694.85,638.1,774.55,757.9,753.35,704.7,
666.8,568.55,653.1,704.05,709.6,726.9,697.15)

x5 <- c(13.2, 14.11,15.68,10.53,11,11.31,11.96,12.58,10.66,10.85,11.41,11.91,12.85,13.58,14.21,15.56,15.83,16.41,13.1,13.63,14.51,15.38,
16.1,16.73,10.58,11.28,11.91,12.65,14.06)

Answer 1

Step-1: Type the data in R

> y <- c(271.8, 264,238.8,230.7,251.6,257.9,263.9,266.5,229.1,239.3,258,257.6,267.3,267,259.6,240.4,227.2,196,278.7,272.3,267.4,254.5,224.7,181.5,227.5,253.6,263,265.8,263.8)

>

> x1 <- c(783.35,748.45,684.45,827.8,860.45,875.15,909.45,905.55,756,769.35,793.5,801.65,819.65,808.55,774.95,711.85,694.85,638.1,774.55,757.9,753.35,704.7,666.8,568.55,653.1,704.05,709.6,726.9,697.15)

>

> x5 <- c(13.2,14.11,15.68,10.53,11,11.31,11.96,12.58,10.66,10.85,11.41,11.91,12.85,13.58,14.21,15.56,15.83,16.41,13.1,13.63,14.51,15.38,16.1,16.73,10.58,11.28,11.91,12.65,14.06)

Step-3: Make a normal Probability Plot using studentized residuals

> plot(model,which=2)

Step-4: Plotting residuals versus predicted response yhat

> plot(model,which=1)

Step-5: Plotting Residuals versus each regressor

> plot(x1,model$res)

> plot(x5,model$res)

Step-6: Partial regression plots of residuals vs. regressors

> library(asbio)

> partial.resid.plot(model)