IS
804 |
Advanced Experimental Design Methodology
This course has the objective of introducing the student to some of the issues involved in analyzing and interpreting data that results from observations or measurements taken during experiments. The intent is to acquaint you with the logic of experimental design and with the methods for interpreting the outcomes of experiments. The course will not teach you to use a statistical package such as SAS or SPSS. Rather, the course will give you the tools to determine the adequacy of any statistical software product and the legitimacy of the conclusions as they relate to your particular experimental and analytical requirements. The field of inferential statistics is dynamic and lively. It is much more complicated and controversial than learning simple-minded algorithms to apply uncritically to a set of data. It is also hugely challenging intellectually and a lot of fun. Accordingly, the course will emphasize solving problems that illustrate the underlying theories that govern the confidence that an investigator may have in reaching conclusions about the effects of various treatments on dependent variables. An appreciation of these issues will also provide you with the analytical tools to evaluate the conclusions of published experimental research and to design and evaluate your own research. All of the assignments in this course may be done by hand, although you are free to use whatever statistical software product that you want, as long as you can show the class members that the software does what it claims to do. This is not a lecture course. This is a seminar course for doctoral and master's degree students. Students will be assigned sections of the textbook to discuss and problems from the textbook to present to the class. Most classes will be devoted to presentations and discussions of problems, and solutions to the problems will be handed in as homework. Some classes will be devoted to reading classic and timely articles from the research literature that illustrate the data analysis techniques under consideration in this course. Past experience suggests that students should plan to spend at least 6 - 8 hours per week to complete the work in this course. This is, however, a level of effort course. Learning about research methods is never finished. Regular class attendance is a requirement. The course format assumes that face-to-face interaction with peers is a powerful motivator and facilitator to achieve mastery in this content domain. The
textbook for this course will be the following: The above information presents a general overview of the course. The requirements for a specific section of the course may differ somewhat from these guidelines, but the general framework will remain the same as presented here. The course syllabus will be posted on the Bb site. Please contact the instructor for additional information. E-mail: Henry H. Emurian Here are the student course evaluations for the instructor's Spring 2008 section of IS 804: Course Evaluations |