Entry Test for Statistical/Data Science class

Question

If there is a Data Science class (for final year high school students, not necessarily from the same school) with the following syllabus:

• Python programming (first 3 meetings)
• Data cleaning and Twitter Data visualization using Matplotlib (4 meetings)
• Probability & Statistics Theory, Normal Distribution, and the Central Limit Theorem (2 meetings)
• Bootstrap Algorithm (2 meetings)
• Some Advanced methods: Clustering, classification and regression trees (CART) (4 meetings)

My question is, how should the entry test be? (the test questions)

or better not give test? since we will teach from basic

I have initial idea that is to give test that includes basic calculus such as application of derivatives (like graphing a function etc) to test their mental ability to visualize abstract math concept. I wonder better approaches. The test should not be restrictive.

Answer 1

Consider the following papers:

• Johnson, Marianne, and Eric Kuennen. "Basic math skills and performance in an introductory statistics course." Journal of Statistics Education 14.2 (2006).
• Lunsford, M. Leigh, and Phillip Poplin. "From research to practice: Basic mathematics skills and success in introductory statistics." Journal of Statistics Education 19.1 (2011).

These feature a multiple-choice diagnostic test used at the start of a statistics course, with various data and conclusions drawn from the results. The test is given in its entirety in each paper. The Johnson paper uses a 15-question test, and the Lunsford paper builds on it with an additional 5 questions. I've used this as the basis for a first-day diagnostic in my community-college elementary statistics course for several years. I find that it has a small amount of predictive power with regard to final exam scores (R^2 = 0.13, N = 238).