SAS to R Notes

How I did part of a SAS assignment in R

The residual plot in SAS was corrupted, luckily I was able to recreate it in R. (And actually it looks better in R too.)

# read in data from file 
gpa.data <- read.table("GPA.txt");
# create multiple linear regression model
gpa.fit <- lm(V4 ~ V1 + V2 + V3 + V5 + V6 + V7 + V8, data=gpa.data)
# save residuals to a variable
gpa.resid <- residuals(gpa.fit)
# save Predicted values to a variable
gpa.yhat <- fitted.values(gpa.fit)

# create png file, that plot will be saved to.
#png("resid.png")
# create a plot of residuals vs predicted values
plot(gpa.yhat,gpa.resid, ylab="Residuals", xlab="Predicted Values of Cum GPA", main="Plot of Residuals*Predicted Values")
# create a line#
abline(0,0)
# write plot to file
#dev.off()

resid.png

ANOVA table of the Multiple Regression Model

anova(gpa.fit)

Analysis of Variance Table

Response: V4 Df Sum Sq Mean Sq F value Pr(>F)
V1 1 0.567 0.5669 1.8709 0.172001
V2 1 26.488 26.4877 87.4135 <2.2e-16 *** V3 1 9.096 9.0964 30.0194 6.839e-08 *** V5 1 2.446 2.4459 8.0717 0.004683 ** V6 1 1.032 1.0324 3.4069 0.065524 .
V7 1 0.020 0.0199 0.0655 0.798068
V8 1 0.278 0.2784 0.9187 0.338288
Residuals 492 149.084 0.3030

codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

Summary of Linear Regression Model

summary(gpa.fit)

Call: lm(formula = V4 ~ V1 + V2 + V3 + V5 + V6 + V7 + V8, data = gpa.data)

Residuals: Min 1Q Median 3Q Max -3.3345 -0.3387 -0.0059 0.3429 1.9661

Coefficients: Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.7792451 0.5165056 3.445 0.00062 *** V1 -0.0383924 0.0527532 -0.728 0.46710
V2 0.2716557 0.0417213 6.511 1.84e-10 *** V3 0.0010404 0.0003173 3.279 0.00111 ** V5 0.0010332 0.0003425 3.016 0.00269 ** V6 -0.0391177 0.0239319 -1.635 0.10279
V7 -0.0006554 0.0028471 -0.230 0.81805
V8 -0.0054118 0.0056462 -0.958 0.33829

codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5505 on 492 degrees of freedom Multiple R-squared: 0.2112, Adjusted R-squared: 0.2 F-statistic: 18.82 on 7 and 492 DF, p-value: < 2.2e-16