Data on the body weight and height of house cats

cats <- read.csv('https://raw.githubusercontent.com/ntlrs/citibikedata/master/catsM.csv?token=APwdEzOEHVzRfz7R9eBA2_iBed7NS8heks5a4TdAwA%3D%3D', header = TRUE)
head(cats)
##   X Sex Bwt  Hwt
## 1 1   M 2.0  6.5
## 2 2   M 2.0  6.5
## 3 3   M 2.1 10.1
## 4 4   M 2.2  7.2
## 5 5   M 2.2  7.6
## 6 6   M 2.2  7.9

Filter the data to only include arable land from 1961 and 2015.

cats <- cats[c(2:4)]
colnames(cats) <- c("sex", "body weight", "height")
head(cats)
##   sex body weight height
## 1   M         2.0    6.5
## 2   M         2.0    6.5
## 3   M         2.1   10.1
## 4   M         2.2    7.2
## 5   M         2.2    7.6
## 6   M         2.2    7.9
plot(cats$`body weight`, cats$height, xlab = "body weight of male house cats", ylab = "height of male house cats")
catsaverage <- lm(cats$height~cats$`body weight`)
abline(catsaverage)

summary(catsaverage)
## 
## Call:
## lm(formula = cats$height ~ cats$`body weight`)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.7728 -1.0478 -0.2976  0.9835  4.8646 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)    
## (Intercept)         -1.1841     0.9983  -1.186    0.239    
## cats$`body weight`   4.3127     0.3399  12.688   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.557 on 95 degrees of freedom
## Multiple R-squared:  0.6289, Adjusted R-squared:  0.625 
## F-statistic:   161 on 1 and 95 DF,  p-value: < 2.2e-16

The value is very small, indicating that there is a correlation between a house cats height and weight.

plot(fitted(catsaverage), resid(catsaverage))

qqnorm(resid(catsaverage))
qqline(resid(catsaverage))