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In my earlier post I carried out an analysis of the Space Shuttle Challenger disaster using Python’s statistical library, statsmodels. That blog post can be read here:- https://medium.com/@tracyrenee61/analyse-space-shuttle-challengers-o-ring-damage-using-python-and-statsmodels-b2fd4aad800a
In this post I intend to perform the same type of analysis, but in the R programming language. R is a programming language written specifically with statistics in mind, while Python is an all purpose language.
R has many statistical and graphical functions inbuilt into the programming language, while Python has to rely on importing libraries to achieve the same things that R can accomplish as a standalone language.
R has many practice datasets inbuilt into the language, while Python does not.
I was not able to find a suitable csv file to work with, so I hard coded the dataframe, oring, into the program, as seen below.
I used the attach() function to attach the dataframe to the program, thereby enabling me to reference the column names without first naming the dataframe:-
