data(mtcars)
head(mtcars)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
# dependent variable - mpg = mpg
# independent variable - weight = wt
plot(mtcars$wt, mtcars$mpg, xlab = "Weight", ylab = "MPG")
y-intercept is 37.285
slope is -5.344
The final regression model is:
mpg = 37.285 - 5.344*wt
car_lm <- lm(mpg ~ wt, data=mtcars)
car_lm
##
## Call:
## lm(formula = mpg ~ wt, data = mtcars)
##
## Coefficients:
## (Intercept) wt
## 37.285 -5.344
summary(car_lm)
##
## Call:
## lm(formula = mpg ~ wt, data = mtcars)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.5432 -2.3647 -0.1252 1.4096 6.8727
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 37.2851 1.8776 19.858 < 2e-16 ***
## wt -5.3445 0.5591 -9.559 1.29e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.046 on 30 degrees of freedom
## Multiple R-squared: 0.7528, Adjusted R-squared: 0.7446
## F-statistic: 91.38 on 1 and 30 DF, p-value: 1.294e-10
The reported R2 of 0.7528 for this model means that 75.28% of the variability in mpg is explained by the variation in weight.
The residuals are not uniformly distributed.
Overall, the Q-Q plot follow a straight line, but we can see the right end diverge from the line. This suggest the distribution’s right tail is “heavier” than what we would expect from a normal distribution. This pattern is indicative of a right-skewed distribution.
plot(fitted(car_lm),resid(car_lm))
qqnorm(resid(car_lm))
qqline(resid(car_lm))
par(mfrow=c(2,2))
plot(car_lm)