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Volume 15 (2007)

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An International Journal on the Teaching and Learning of Statistics

JSE Volume 15, Number 2 Abstracts

Singfat Chu
Some Initiatives in a Business Forecasting Course

The paper reports some initiatives to freshen up the typical undergraduate business forecasting course. These include (1) students doing research and presentations on contemporary tools and industry practices such as neural networks and collaborative forecasting (2) insertion of Logistic Regression in the curriculum (3) productive use of applets available on the Internet to convey abstract concepts underlying ARIMA models and (4) showcasing forecasting tools in timely or familiar applications. These initiatives align with the best practices framed across the “Making Statistics More Effective in Schools of Business” (MSMESB) conferences. Course experiences and student feedback are also discussed.

Key Words: ARIMA, Logistic Regression, Pedagogy

Nilupa S. Gunaratna, Craig A. Johnson, and John R. Stevens
Service-Learning for Graduate Students through a Student-run Consulting Program

Statistics in the Community (STATCOM) is a student-run statistical consulting program that has been serving its local community since 2001. Directed and staffed by graduate students from Purdue University’s Department of Statistics, it provides professional consulting services to governmental and nonprofit groups free of charge. Students work in teams to help community clients address specific problems and needs. Past clients include school corporations, libraries, community assistance programs, and the city of West Lafayette. Participation in STATCOM allows students to apply statistical concepts and classroom material to solve real problems. It also develops skills in leadership, management, and written and oral communication of results to the general public. Though important for any future career in statistics, these skills are not typically emphasized in graduate courses, research, or the on-campus academic consulting service. The university and academic department also benefit through increased interaction and visibility in the local community. STATCOM can serve as a model for integrating service learning into graduate statistical education at other colleges and universities.

Keywords:Community service; Graduate Education; Service-learning

Debra L. Hydorn
Community Service-Learning in Statistics: Course Design and Assessment

Service-learning projects are a useful method for students to learn both the practice and value of statistical methods. Effective service learning, however, depends on several factors and can be implemented according to a variety of models. In this article, different models for incorporating service-learning in statistics courses are presented along with example statistics courses. Principles for good service-learning practice will also be presented as a means for assessing the quality of a service-learning course component.

Keywords:Assessment; Experiential learning; Service-learning; Statistics education

Gary D. Kader and Mike Perry
Variability for Categorical Variables

Introductory statistics textbooks rarely discuss the concept of variability for a categorical variable and thus, in this case, do not provide a measure of variability. The impression is thus given that there is no measurement of variability for a categorical variable. A measure of variability depends on the concept of variability. Research has shown that "unalikeability" is a more natural concept than "variation about the mean" for many students. A "coefficient of unalikeablity" can be used to measure this type of variability. Variability in categorical data is different from variability in quantitative data. This paper develops the coefficient of unalikeability as a measure of categorical variability.

Keywords: Variability, Categorical Variable, Unalikeability

Eric D. Nordmoe
Service-Learning in Introductory Statistics at Kalamazoo College

Kalamazoo College is a selective, liberal arts college located in Kalamazoo, Michigan with total enrollment of approximately 1200 students. The academic calendar is comprised of three 10-week quarters, each of which is followed by one week for final examinations. Kalamazoo College is distinguished by its four-fold academic program known as the “K-Plan”: (1) Rigorous liberal arts coursework, (2) study abroad, (3) career development, and (4) the senior individualized project. With the inception of the K-Plan over 40 years ago, experiential education has long characterized the College student experience, especially with respect to the last three components listed above. Over the past ten years, the on-campus experience of Kalamazoo College students has also become more experiential in nature as a substantial proportion of courses now have significant service-learning components.

Laurie H. Rubel
The Availability Heuristic: A Redux

This article reports on a subset of results from a larger study which examined middle and high school students’ probabilistic reasoning. Students in grades 5, 7, 9, and 11 at a boys’ school (n=173) completed a Probability Inventory, which required students to answer and justify their responses to ten items. Supplemental clinical interviews were conducted with 33 of the students. This article describes students’ specific reasoning strategies to a task familiar from the literature (Tversky and Kahneman, 1973). The results call into question the dominance of the availability heuristic among school students and present other frameworks of student reasoning.

Keywords:availability heuristic, combinatorial thinking, middle school, high school

From Research to Practice

Joy Jordan
The Application of Statistics Education Research in My Classroom

A collaborative, statistics education research project (Lovett, 2001) is discussed. Some results of the project were applied in the computer lab sessions of my elementary statistics course. I detail the process of applying these research results, as well as the use of knowledge surveys. Furthermore, I give general suggestions to teachers who want to put educational research results into effective use in their own classes.

Key Words: Computer lab, Data analysis, Knowledge survey, Research application

Datasets and Stories

Michael Huber and Andrew Glen
Evaluating Aptness of a Regression Model

The data for 104 software projects is used to develop a linear regression model that uses function points (a measure of software project size) to predict development effort. The data set is particularly interesting in that it violates several of the assumptions required of a linear model; but when the data are transformed, the data set satisfies those assumptions. In addition to graphical techniques for evaluating model aptness, specific tests for normality of the error terms and for slope are demonstrated. The data set makes for an excellent case problem for demonstrating the development and evaluation of a linear regression model.

Key Words: data transformation; residual analysis; linear model assumptions; linear regression

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