Module 2: Basic Summary Statistics in R

Fair warning, we are NOT statisticians. So when we say ‘basic’ we mean very simple summary statistics to perform initial data exploration. In Video #2, you will go through a walkthrough of several data files in R. Below are some files that will be helpful to download and use as you walk through the video. You will also be asked to pause or explore data after the video completes on your own. This step is optional. If you feel you need a basic refresher on statistics, here is a nice video review of Statistics for Science.

Video #2

In this video we will be working with two files in R: USpop.csv and BodyFat.csv. Both files are included in the data tarball located in the raw_data directory.

IF you are well practiced with reading data into R, feel free to read in our existing data object.

Make an R Notebook for this walk through tutorial to save all the code you will be learning. We will cover:

• Reading in datasets
• Various ways to subset data
• Basic Summary Statistics
  • mean and sd
  • range
  • summary
• Exploring data visually
  • Using hist function
  • Using plot function
• Testing for a statistial correlation

Walk-through code

• R Markdown from video (Slideshow)

Data Files

• USPop.csv
• BodyFat.csv

Associated code and data files are also within the compressed data file.

Recommended R in Action Readings that cover the material in this video:

• Chapter 2: pgs. 20-45
• Parts of Chapter: 7.1.1: 138-139; 7.2.2: 151-152; 7.3 Correlations pgs: 153-158

Recommended Follow Up:

• To better understand the statistics behind a Pearson’s correlation test, here is a simple video that covers this topic in more depth. Note, it is beyond the scope of this course to distinguish between different correlation methods, but you may be interested in researching the Spearman’s correlation test as an alternative method, which has different statistical assumptions than the Pearson’s correlation test.
• While the walk-through and the above video cover correlation, the walk through also revisits p-values, which you may already be familiar with. Still, if you want a good refresher from a more statistical perspective, we find this video on the Chi-Square test to be very helpful. Although it is not specific to statistical correlation tests, it still helps to reinforce some of the statistical concepts covered in the walk through video.
• A similar video, which covers the Student’s t-test is also helpful in reviewing a concept not covered here, but that you might need to use in R. The video uses excel, but this is quite simple to implement in R as well.

Next page:

Module 3: Data manipulation in R