6 Linear model

While the assumtions of a linear model are never perfectly met, we must still check if they are reasonable assumtions to work with.

6.1

## Data from  https://github.com/thomas-haslwanter/statsintro_python/blob/master/ISP/Code_Quantlets/08_TestsMeanValues/anovaOneway/galton.csv
tab<-read.csv("data/galton.csv")
head(tab)

##   family father mother sex height nkids
## 1      1   78.5   67.0   M   73.2     4
## 2      1   78.5   67.0   F   69.2     4
## 3      1   78.5   67.0   F   69.0     4
## 4      1   78.5   67.0   F   69.0     4
## 5      2   75.5   66.5   M   73.5     4
## 6      2   75.5   66.5   M   72.5     4

6.2 Extract male data

tab_son = tab[tab$sex=="M", ]
head(tab_son)

##    family father mother sex height nkids
## 1       1   78.5   67.0   M   73.2     4
## 5       2   75.5   66.5   M   73.5     4
## 6       2   75.5   66.5   M   72.5     4
## 9       3   75.0   64.0   M   71.0     2
## 11      4   75.0   64.0   M   70.5     5
## 12      4   75.0   64.0   M   68.5     5

plot(father~height, data=tab_son)

6.3 Reference

How to apply Linear Regression in R: https://datascienceplus.com/how-to-apply-linear-regression-in-r/

R for Data Science: https://r4ds.had.co.nz/model-basics.html#a-simple-model