Case Study 7: Counting names in scripture


In 1978 Susan Easton Black penned an article in the Ensign title Even statistically, he is the dominant figure of the Book of Mormon. which makes some statistical claims about the Book of Mormon. With our “string” skills we are going to check her result and build an improved statistic using using number of words between references.


This reading will help you complete the tasks below.


  • [ ] Get the scripture and savior name data into R
    • [ ] Download the data from
    • [ ] Read in the .csv file that was in the zip file and examine the structure of the data
    • [ ] Use read_rds(gzcon(url(""))) to download and load the Savior names table into R
  • [ ] Use the list of Savior names and the Book of Mormon verses to figure out the average number of words between references to the Savior
    • [ ] Find each instance of a Savior name in the Book of Mormon
    • [ ] Split on those instances and then count the number of words between each instance
    • [ ] Use the example code below for some hints on how to tackle this task
  • [ ] Report the average number of words between each Savior name
  • [ ] Create an .Rmd file with 1-2 paragraphs summarizing your graphic that shows how the distance between Savior names is distributed across the Book of Mormon
  • [ ] Compile your .md and .html file into your git repository
  • [ ] Find two other student’s compiled files in their repository and provide feedback using the issues feature in GitHub (If they already have three issues find a different student to critique)
  • [ ] Address 1-2 of the issues posted on your project and push the updates to GitHub


# To get the standard works data
scriptures <- rio::import("")

# to get the Savior names
bmnames <- read_rds(gzcon(url("")))

# your script might use the following functions