Practical R 4

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.

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

• 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