



B. The scatter diagram which represent the data is in option A). Hence, it is the correct option.
A simple linear regression model does not appear to be appropriate here.
b) Simple regression model equation:
y = -513.6 + 308.4 * Capacity
The standardised residual plot of the regression equation is in option D)
As it is not distributed randomly around 0, linear regression does not seem to be appropriate here.
c) y = 14218.6 + (-5847.7) Capacity + 638.3 (CapacitySq)
Yes, we prefer the equation in part c) because the R-squared value is more in part c) model and the curve fits more to our values.
e) We could fit a polynomial equation with more powers of capacity in the regression. It also depends on the options what we have.
Note: All the above analysis has been done in R. The codes are:
aa<-read.csv("data.csv")
model1 <- lm(LP~C, data = aa)
summary(model1)
plot(model1)
model2 <- lm(LP~I(C^2) + C, data = aa)
summary(model2)
plot(model2)
Capacity List Price Maytag High-Efficiency Top Loading Washer with Steanm Samsung High-Efficiency Top Loading Washer with Active 4.8 $749 Wash and Integrated Touch Controls Whirlpool High-Efficiency...