I am planning to develop a course which I tentatively call as 'Quantitative Reasoning'. The goal of the course is to equip a typical undergraduate student with sound quantitative reasoning skills so that they can critically evaluate statistical and related quantitative claims they may encounter as part of their personal/professional lives.
In contrast to the traditional 'Intro to Statistics' type of courses the focus of this course will not be on derivation of formulas, use of statistical tests etc but on interpretation and understanding of statistical concepts. Towards that end I have developed a rough list of topics that I would like to cover in this course:
- Logic of hypothesis tests
- Interpretation of p-values and clarify common misconceptions.
- Bayesian statistics and its relationship to frequency statistics (at an informal level)
- Conditions required for causality
- How to assess/test for causality?
- Advantages & disadvantages of experiments, surveys etc
In light of the above, I have three questions:
What else should you think I should include/exclude from such a course?
Are there any textbooks that may be useful given the above goal?
Are you aware of any other course that attempts to accomplish the above? Links to syllabus would be very helpful.
If it matters, the target student for the above course is an undergraduate student in the US possibly at the freshman or sophomore level.