R Statistics Cookbook

How to do it...

In this exercise, we will simulate some data, and compute the estimates using both the lm function and doing the matrix calculations ourselves. This is very useful for understanding the inner mechanics behind the lm function:

1. We first generate some data, and do a simple linear regression using lm:

library(sjPlot)clients <- read.csv("./clients.csv")model1 <- lm(Sales ~ Strategy + (Client) + (Salesman),data=clients)tab_model(model1)

The lm output reports an intercept and two coefficients that are very close to the ones we used (40,1,1). The standard errors can be interpreted as the (im)precision of each estimate, and the t-values ...