Synopsis
Chapter 1: Getting Up and Running with R
Chapter 2: Getting Data into R
Chapter 3: Project 1: Launching, Analyzing, and Reporting a Survey using R and LimeSurvey
Chapter 4: Project 2: Advanced Statistical Analysis using R and Mouselab Web
Chapter 5: R in Everyday Life
Chapter 6: Project 3: The R Form Mailer
Chapter 7: Project 4: The R Powered Presentation
Chapter 8: R Anywhere
Chapter 9: Project 5: The Change Alert!
Chapter 10: Project 6: The R Personal Assistant
DETAILED VIEW BELOW
Chapter 1: Getting Up and Running with R
Chapter Goal:
• Explain what R is, and what R isn't
• Explain the R landscape - it's open source nature and the various ways people use it.
• Explain how R is installed, what types of systems it runs on, and how the user interacts with it.
• Explain the basic R script, running basic commands in R (e.g., a "Hello World") and basic computations.Chapter 2: Feed the Beast: Getting Data into R
• Explain the different types of data that R can work with, and how that data is stored.
• Explain the basics of connecting R to flat files, database files, database servers, and published data on the internet.
• Give examples for downloading data directly from Google Sheets, websites, and more directly from R.
• Give examples of basic data scraping with R.
• Explain writing of data objects to native RData format as well as other formats for interchangeable use.
Chapter 3: Recipe 1: Launching, Analyzing, and Reporting a Survey using R and LimeSurvey
• Explain a real-world scenario: A survey project applicable to market research.
• Discuss an open-source tool, LimeSurvey, that can be used to create a survey, collect responses, and download those responses into R.
• Bring the data into R and run basic summary statistics on the data.
• Take those analyses farther into inferential statistics (Linear Regression).
Chapter 4: Recipe 2: Advanced Statistical Analysis using R and Mouselab Web
• A deeper data scenario than Chapter 3 discussing how Mouselab Web (an open source tool) can be used to track how people view products and services and make decisions.
• Introduces advanced statistical design using Linear Mixed-methods regressions.
• Also introduces the idea of R packages, and the perils of using packages (e.g., concerns over future-proofing). This chapter is a very deep concept that will be presented accessibly, so that readers learn the takeaways regarding how R works and how to futureproof your R projects, but also get a bit of a unique project applicable to psychology and market research.
Chapter 5: R in Everyday Life
• Perhaps you're not a statistician, you just want R to be useful to you in your job. This chapter discusses how R can be used to automate...
o Data formatting
o Data manipulation
o Data reporting
• This chapter also talks about how users can write custom functions in R to speed up their workflows.
• Finally this chapter talks about how to export results from R into common desktop software such as Microsoft Office.
Chapter 6: Recipe 3: The R Form Mailer
• Mail Merge is a great tool in Microsoft Office, but it's entirely graphically driven - point and click, drag and drop. What if you could script it?• This recipe discusses scripting a Mail Merge type activity - sending custom emails with report information directly from R through an email server.
• Along the way we learn a bit more about data manipulation by taking long format data (sales figures) and
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