Abstract
Case study method is one of the widely used methods in MBA programs around the world. Its effectiveness has been demonstrated for marketing and management courses. It is rather difficult to implement case study method for quantitative courses (such as a managerial statistics course). The challenge is to use this approach for basic statistics course assuming that students did not have statistics course before. In this paper we discuss a case study related to evaluation of study programs in Latvian universities and colleges in 2012. In addition, three real-life examples from different areas of statistics are also analyzed. The case study and real-life examples were gradually introduced in a business statistics course during the period of several years. Analysis of the results of the survey among students showed that not only the interest to the course has risen but alsothe willingness to apply statistical methods at work. Keywords: Real-life problem; business statistics; measurement scales; regression analysis; sample.
Highlights
Teaching statistics for business majors is not an easy task
Some attempts are made in the past to use case study approach in multiple regression: (Klibanoff et al, 2006), but knowledge of basic statistics is assumed as a prerequisite for the course
The role of examples in this case becomes crucial: (Hanh & Doganaksoy, 2010). Business education includes such courses as economics, marketing, finances. It would be very beneficial for business students to see the link between the concepts that are discussed in statistics course and other courses taught at MBA programs
Summary
Teaching statistics for business majors is not an easy task. Some students do not have strong background in mathematics, some are not so interested in the course since it is viewed as “very theoretical” and from their point of view has little practical value. This allows an instructor to demonstrate that we can extend (in some cases) the class of regression models in applications beyond linear models without considerable increase in computational complexity In both examples the major objective is to identify the most important predictors, no attempt is made by the authors to predict quantitatively the dependent variables since the coefficient of determination was quite low (which is usually the case in practice). These examples are gradually introduced in managerial statistics course taught at Riga Business School during the last few years. Available from: www.prosoc.eu the results of the surveys shows that the proportion of students claiming that they have learned a lot during the course has increased considerably
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