Practical R 4: Applying R to Data Manipulation, Processing and Integration

Chapter 1: Getting Up and Running with RChapter 2: Getting Data into RChapter 3: Project 1: Launching, Analyzing, and Reporting a Survey using R and LimeSurveyChapter 4: Project 2: Advanced Statistical Analysis using R and Mouselab WebChapter 5: R in Everyday LifeChapter 6: Project 3: The R Form MailerChapter 7: Project 4: The R Powered PresentationChapter 8: R AnywhereChapter 9: Project 5: The Change Alert!Chapter 10: Project 6: The R Personal Assistant

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Chapter 1: Getting Up and Running with RChapter 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 formattingo Data manipulationo 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