OpenIntro Statistics Dataset - ucla_textbooks_f18

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dataset-578349888.csv 31.57 KB
Dataset License
Documentation License
No license (All rights reserved)

This dataset was taken from the list of OpenIntro dataset files found at

OpenIntro features a number of free books that can be used in high school and AP statistics courses. The license on these datasets is currently unknown. You can find out more about OpenIntro at


Sample of UCLA course textbooks for Fall 2018

A sample of courses were collected from UCLA from Fall 2018, and the corresponding textbook prices were collected from the UCLA bookstore and also from Amazon. A past data set was collected from UCLA courses in Spring 2010, and Amazon at that time was found to be almost uniformly lower than those of the UCLA bookstore's. Now in 2018, the UCLA bookstore is about even with Amazon on the vast majority of titles, and there is no statistical difference in the sample data.


  • year - Year the course was offered.
  • term - Term the course was offered.
  • subject - Subject.
  • subject_abbr - Subject abbreviation, if any.
  • course - Course name.
  • course_num - Course number, complete.
  • course_numeric - Course number, numeric only.
  • seminar - Boolean for if this is a seminar course.
  • ind_study - Boolean for if this is some form of independent study.
  • apprenticeship - Boolean for if this is an apprenticeship.
  • internship - Boolean for if this is an internship.
  • honors_contracts - Boolean for if this is an honors contracts course.
  • laboratory - Boolean for if this is a lab.
  • special_topic - Boolean for if this is any of the special types of courses listed.
  • textbook_isbn - Textbook ISBN.
  • bookstore_new - New price at the UCLA bookstore.
  • bookstore_used - Used price at the UCLA bookstore.
  • amazon_new - New price sold by Amazon.
  • amazon_used - Used price sold by Amazon.
  • notes - Any relevant notes.


The most expensive book required for the course was generally used. The reason why we advocate for using raw amount differences instead of percent differences is that a 20\ to a 20\ meaning a small and largely insignificant price difference on low-priced books would balance numerically (but not in a practical sense) a moderate but important price difference on more expensive books. So while this tends to result in a bit less sensitivity in detecting \emph{some

effect, we believe the absolute difference compares prices in a more meaningful way. Used prices contain the shipping cost but do not contain tax. The used prices are a more nuanced comparison, since these are all 3rd party sellers. Amazon is often more a marketplace than a retail site at this point, and many people buy from 3rd party sellers on Amazon now without realizing it. The relationship Amazon has with 3rd party sellers is also challenging. Given the frequently changing dynamics in this space, we don't think any analysis here will be very reliable for long term insights since products from these sellers changes frequently in quantity and price. For this reason, we focus only on new books sold directly by Amazon in our comparison. In a future round of data collection, it may be interesting to explore whether the dynamics have changed in the used market.}


Taken from:

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