Check https://pythonforscientist.blogspot.com/2021/ for reference
Data set in https://cutt.ly/BEQUlnA
>>>lin_reg <- lm(file_car$dist~file_car$speed)
#code above creates linear regression lm(y~x)
>>>lin_reg
>>> plot(file_car$speed,file_car$dist)
Check https://pythonforscientist.blogspot.com/2021/ for reference
Data set in https://cutt.ly/BEQUlnA
>>>lin_reg <- lm(file_car$dist~file_car$speed)
#code above creates linear regression lm(y~x)
>>>lin_reg
>>> plot(file_car$speed,file_car$dist)
go to https://cutt.ly/BEQUlnA for downloading the csv file.
#comments after the hash #
#Download the csv to process the data and begin with your use of R
The commands are shown after the ">>>" you do not need to wirte the ">>>" just "getwd()"
another useful command is "dir()" this shows all folders and files on the current folder
#getwd() shows where the working directory of R is located
>>>getwd()
>>> head(file_car)
X speed dist
1 1 4 2
2 2 4 10
3 3 7 4
4 4 7 22
5 5 8 16
6 6 9 10
#head shows the first entry rows and its variables
#tail shows the last rows showing the respective columns
#summary gives a general mean and median of all data
###conclusion and Notes
"Overall R is a powerful language tailored for statisticians and data scientist you can begin with this easy blog in following projects and tutorials I will explain more to use the full capacities and uses for your application. Welcome to the R world and enjoy your journey."
Notes the R software here is an open source that is why is very widespread and attractive
R has a more visual interface GUI that will be shown in future tutorials