Cobb and Moore (1997) call for the design of a better undergraduate mathematical
statistics course that both strengthens students’ mathematical skills and integrates data analysis into the curriculum. Others have called for similar courses (Foster & Smith, 1969, Hogg et al., 1985, Kempthorne, 1980, Moore & Roberts, 1989, Mosteller, 1988, Petruccelli et al., 1995, Whitney & Urquhart, 1990). However, it is a challenge to bring data analysis skills into the mathematical statistics course. We advocate that we are better able to achieve this integration by including case studies in the curriculum.
Nolan and Speed (1999) have developed a course that teaches mathematical statistics through in-depth case studies. Our approach integrates statistical theory and practice in a way not commonly found in an undergraduate course in mathematical statistics. Each case study centers on a scientific question; it contains a dataset to address the question, and we develop statistical theory in order to answer this question. There are three salient aspects to our case studies approach:
- The problem central to the case is introduced first, and background information on the problem and a description of data collected to address the problem are provided before any relevant statistical theory is discussed.
- The solution to the problem raised in the case study is not provided to the students. In fact, there are many possible solutions, which use many different types of analyses.
- The student plays the role of a consultant, analyst, government official, textbook author, etc. in developing and presenting the solution to the problem.