Operations Research Management Science Today - June 2001 - Issues in Education

<BODY bgcolor="#ffffff" link="cc0000" vlink="cc0000" text="#000000"> <img src="../cleardot.gif" width=1 height=1 vspace=4 border=0><br>   <table border=0 cellspacing=0 cellpadding=0 width=480><tr valign=top> <td width=10><img src="../cleardot.gif" width=1 height=1 hspace=4 border=0></td> <td width=470> <FONT face="verdana, arial, helvetica" SIZE=2><B><I><A HREF="../../ORMS.shtml" TARGET="_top">OR/MS Today</A> - June 2001</I></B></font><BR> <hr size="1"> <img src="cleardot.gif" width=1 height=1 vspace=4 border=0><br> <font face="times new roman, times"> <img src="../cleardot.gif" width=1 height=1 vspace=4 border=0><br> <FONT face="verdana, arial, helvetica" SIZE=2><B>Issues in Education</B></FONT><br> <IMG SRC="../barbluehook.gif" WIDTH="468" HEIGHT="4"><br> <img src="../cleardot.gif" width=1 height=1 vspace=8 border=0><br> <FONT SIZE="+2"><B>Learning Statistics in Context</B></FONT><BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> <FONT face="verdana, arial, helvetica" SIZE=2><B>By Greg M. Lepak</B></FONT><br> <hr size="1"> <img src="../cleardot.gif" width=1 height=1 vspace=12 border=0><br>   Statistics is the science of data. To be "statistically" the weakest link, in the quiz show with the same name, implies that data on contestants' performances are produced and analyzed to identify the least measure of performance. At the end of each round the charming host discloses in no uncertain terms which of the contestants is statistically the weakest link. However, the statistics remain less clear. Is there a single statistic, the simple count of the number of questions answered incorrectly by each contestant? Or is the analysis based on several measures to include, for instance, the amount of money banked by a contestant, and maybe even the level of question answered correctly in the link? What are the criteria? Are the criteria used sequentially in the analysis or is the result derived from a function that combines the various measures? The answer to some of these questions may describe the context for this situation that frames the statistical conclusion.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> We are inundated with statistical results presented as additional knowledge and guidance for us to use in our day-to-day decision-making. The type of data, the classification and the analysis, even in the most general forms, are rarely communicated with the results. As a result, the context in which the statistical result can be of use is often ignored, as if it were irrelevant. Statisticians agree that the context drives any statistical analysis and hence greatly influences the interpretation of the results. A statistical result presented without the context of the analysis is not an effective decision-making tool.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> As educators we need to offset this common conception which suggests that statistics is a "black box" where the primary focus in the decision-making process is the "end results." The business curriculum relies heavily on statistics as a decision-making tool and hence should greatly emphasize the context of any statistical analysis. In the introductory statistics and quantitative methods courses we have two possible objectives:<BR> (a) introduce statistics to students who can become proficient in performing statistical analysis and through further training choose it as their career path; and<BR> (b) prepare managers in the various business disciplines, like marketing and finance, to use statistical analysis in their decision-making.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> In both objectives, the context is the key to success. For the first objective, there is an abundance of work in the literature to support the importance of the contextual basis for teaching statistics to would-be statisticians (for example, see the discussions by McDonald, 1999; and Ritter, Starbuck and Hogg, 2001). The remainder of this article focuses on the second objective.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> Getting exposure to statistical analysis in context is even more important for students who will not become trained statisticians. The curriculum should emphasize the dangers and pitfalls of the everyday approach to statistics that focuses on the "end results." Students who receive appropriate training become aware that the analysis is highly dependent on the context. Therefore, their involvement as managers in defining the context for the analysis is crucial in achieving appropriate decisions.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> Highlighting the context in a business statistics curriculum can be achieved through a variety of pedagogical tools that are well documented in the literature. One very valuable tool that we use in our classes is the case approach using real data. There are many benefits resulting from the case approach, e.g., the development of team-based skills, communication skills and critical thinking skills. The single most important benefit of the case approach, however, is that it brings out the context of a particular problem setting and emphasizes that contextual issues drive the analysis.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> Technology makes it feasible to capture in-depth the contextual issues underlying the analysis. The use of spreadsheets and databases makes it possible to easily handle large-scale problems in the classroom. One final tool that we find useful to emphasize the context in a statistical application is simulations and games. In a game setting, students easily appreciate that knowing the context including the parameters, rules and behavior of the simulation increases their chances of making the right decisions.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=6 border=0><br> Managers need to use statistics in their comprehensive form to guide their decisions. A business statistics curriculum needs to emphasize the context not only in the interpretation of statistical analysis but in all aspects of statistics. The data availability, collection and classification as well as the assumptions and the criteria of the analysis should be an integral part of using statistics. The statistical "end result" should be clearly framed in that complete context.<BR> <img src="../cleardot.gif" width=1 height=1 vspace=4 border=0><br> <IMG SRC="../barbluehook.gif" WIDTH="468" HEIGHT="4"><br> <img src="../cleardot.gif" width=1 height=1 vspace=2 border=0><br> <FONT face="verdana, arial, helvetica" SIZE=2><I>Greg M. Lepak (<A HREF="mailto:lepak@mail.lemoyne. edu">lepak@mail.lemoyne.edu</A>) is a professor of statistics and quantitative methods at Le Moyne College, Syracuse, N.Y.</i><BR>  <img src="../cleardot.gif" width=1 height=1 vspace=5 border=0><br>  <img src="../barblue.gif" width=468 height=1 border=0 alt=" "><br> <img src="../cleardot.gif" width=1 height=1 vspace=8 border=0><br> <font face="verdana, arial, helvetica" size="1"> <CENTER><script type="text/javascript"></script> <script type="text/javascript" src="http://pagead2.googlesyndication.com/pagead/show_ads.js"> </script></CENTER><br> <img src="../cleardot.gif" width=1 height=1 vspace=8 border=0><br> <FONT face="verdana, arial, helvetica" SIZE=1> <LI> <A HREF="tocfr.html" Target="_top"><I>Table of Contents</I></A><br> <img src="../cleardot.gif" width=1 height=1 vspace=4 border=0><br> <LI> <A HREF="../../ORMS.shtml" TARGET="_top"><I>OR/MS Today</I> Home Page</A><br>  <img src="../cleardot.gif" width=1 height=1 vspace=8 border=0><br> <img src="../barblue.gif" width=468 height=1 border=0 alt=" "><br> <b><i>OR/MS Today</i></b> copyright © 2001 by <A HREF="http://www.informs.org/" target="_new">the Institute for Operations Research and the Management Sciences</a>. 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