This article is about simple calculation of parameters of linear regression in R script.

If you are interested in linear regression in Excel, click here.

Let´s start with data uploading. In this example we will observe the dependency of sales on number of adds.

number_of_adds = c(10,15,22,8,14,20,32,27)
number_of_sold_products = c(17,27,37,13,25,34,60,49)

Create a data frame from vectors:


Create a linear model from data frame.

mymodel = lm(number_of_sold_products ~ number_of_adds, data = mydata)

Now you can show the model and its parameters:


(Intercept) number_of_adds 
-2.377 1.899

You can also draw it:


What does the results mean?

  • The dots in charts makes quite straight increasing line. This means there is positive linear dependency – the more adds, the bigger sales. 
  • The parameter -2,377 says in which point this line crosses the y axis.
  • The parameter 1,899 describes the steepness of line – the higher, the bigger impact of adds on sales.

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