R for Marketing Research and Analytics

These slides are a companion to the book R for Marketing Research and Analtyics. The book is for:
- Marketing research practitioners seeking to learn R.
- Data scientists interesting in marketing applications.
- Marketing students and academics interested in practical applications.
Companion code files are available at (http://r-marketing.r-forge.r-project.org/), but we suggest you type each line of code, to begin developing your R skills.

About the authors

Dr. Chris Chapman is a Senior Quantitative Experience Researcher for the Google Cloud Platform, based in the Seattle office.

Dr. Elea McDonnell Feit is an Assistant Professor of Marketing at Drexel University and a Senior Fellow of the Wharton Customer Analytics Initiative.

What is R?

“R is a language and environment for statistical computing and graphics.” http://www.r-project.org/about.html

R is:

A programming language (not a “stats program'')
An environment for writing code and handling data
User extensible through add ons and custom code
Open source and freely available
Where new statistics and analytics innovation most often happen first

What is R Not?

R is not:

Intended for point-and-click usage
Designed to hide complexity from the user
Necessarily a fast or easy way to do something that is new to you

Like learning a non-computer human language, R takes time, practice, patience, and application to real problems.

Why R?

If it's hard to learn, why is it worth it?

For some users, R is too much. If you don't like programming, you likely will not like R. On the other hand:

R is optimized for working with data and statistics
The programming language is relatively simple and flexible
1000s of people have contributed additions to R
Once you have mastered something in R, it is easy to automate it and become more and more productive

And

R skills are in very high demand

Why NOT R?

Full control == more complexity
Steep learning curve
Don't try to learn R when time is critical!

And perhaps most importantly:

R is a programming language.
If you have tried computer programming and didn't like it, you probably won't like R

What do you need to use R?

At a minimum:

R binaries from CRAN (Comprehensive R Archive Network)
[http://cran.r-project.org]

Also recommended:

RStudio IDE (integrated development environment)
[http://www.rstudio.com]

RStudio is free and will make your life much easier! To use RStudio, first install R and then install RStudio separately.

Now ...

Make sure R and RStudio are up and running on your systems!

Once it is working for everyone, we'll start with the language.