MAR Chapter 3 Ex 3
ads <- read.csv(file="AdRevenue.csv")
m<-lm(AdRevenue~Circulation,ads)
summary(m)
##
## Call:
## lm(formula = AdRevenue ~ Circulation, data = ads)
##
## Residuals:
## Min 1Q Median 3Q Max
## -147.694 -22.939 -7.845 13.810 131.130
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 99.8095 5.8547 17.05 <2e-16 ***
## Circulation 22.8534 0.9518 24.01 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 42.22 on 68 degrees of freedom
## Multiple R-squared: 0.8945, Adjusted R-squared: 0.8929
## F-statistic: 576.5 on 1 and 68 DF, p-value: < 2.2e-16
confint(m,'Circulation',level=0.95)
## 2.5 % 97.5 %
## Circulation 20.95411 24.75267
plot(ads$Circulation,ads$AdRevenue)
abline(m)
hist(m$residuals)
qqnorm(m$residuals)
qqline(m$residuals)
plot(ads$Circulation,residuals(m))
abline(0,0)
m<-lm(log(AdRevenue)~log(Circulation),ads)
summary(m)
##
## Call:
## lm(formula = log(AdRevenue) ~ log(Circulation), data = ads)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.47022 -0.11142 -0.00532 0.10835 0.42705
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.67473 0.02525 185.16 <2e-16 ***
## log(Circulation) 0.52876 0.02356 22.44 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1768 on 68 degrees of freedom
## Multiple R-squared: 0.881, Adjusted R-squared: 0.8793
## F-statistic: 503.6 on 1 and 68 DF, p-value: < 2.2e-16
confint(m,'log(Circulation)',level=0.95)
## 2.5 % 97.5 %
## log(Circulation) 0.4817413 0.5757747
plot(log(ads$Circulation),log(ads$AdRevenue))
abline(m)
hist(m$residuals)
qqnorm(m$residuals)
qqline(m$residuals)
plot(log(ads$Circulation),residuals(m))
abline(0,0)
