Marlene A. Smith

Developing Case-Based Business Statistics Courses

Abstract We provide guidelines for developing case-based business statistics courses. Specifically, we describe both the benefits and pitfalls of case-based courses, and list resources available for course development. We describe the characteristics of the instructor (and the classroom!) which augur well for case-based teaching.

In the Aftermath of an Acquisition Triggers and Effects on Perceived Organizational Identity

This study examines how the POIs of members of an online retail organization were affected after an acquisition. The authors find that (a) POI is more complex than previously understood, and continuity, change and confusion in POI can coexist. (b) The organizational change reactivated previously unresolved POI issues. (c) The structure of POI includes cognitive, affective, and behavioral dimensions, and changes occurred in these dimensions. (d) Top managers and employees who have more interactions with outsiders in their jobs tend to be more confused and make less POI change than employees who primarily deal with internal operations. Finally, (e) the image of the acquired organization and the change strategies used are triggers of POI confusion and/or change in the acquiring organization. This article highlights the experience of individuals in the acquiring organization and suggests that POI is an important lens for understanding and managing organizational changes.

Choosing among multiple nonlinear non-nested regression models with different dependent variables : An application to money demand

Abstract The linearly-embedded regression model approach of Davidson and MacKinnon (1981) is used to construct joint tests of seven non-nested, autoregressive money demand equations with different regressands. The results support the Holmes-Smyth (1972) hypothesis that taxes affect money demand.

Forecasting emergency department arrivals: a tutorial for emergency department directors.

Abstract This article is a tutorial for emergency department (ED) medical directors needing to anticipate ED arrivals in support of strategic, tactical, and operational planning and activities. The authors demonstrate our regression-based forecasting models based on data obtained from a large teaching hospitals ED. The versatility of the regression analysis is shown to readily accommodate a variety of forecasting situations. Trend regression analysis using annual ED arrival data shows the long-term growth. The monthly and daily variation in ED arrivals is captured using zero/one variables while Fourier regression effectively describes the wavelike patterns observed in hourly ED arrivals. In our study hospital, these forecasting methods uncovered: long-term growth in demand of about 1,000 additional arrivals per year; February was generally the slowest month of the year while July was the busiest month of the year; there were about 20 fewer arrivals on Fridays (the slowest day) than Sundays (the busiest); and arrivals typically peaked at about 10 per hour in the afternoons from 1 p.m. to 6 p.m., approximately. Because similar data are routinely collected by most hospitals and regression analysis software is widely available, the forecasting models described here can serve as an important tool to support a wide range of ED resource planning activities.

Managing Case Discussions in Introductory Business Statistics Classes: Practical Approaches for Instructors

Case discussions have become an integral component of our business statistics courses. We have discovered that case discussion adds enormous benefits to the classroom and learning experience of our students even in a quantitatively based course like statistics. As we read about discussion-based methods, we discovered that the literature is mostly silent about the specific challenges of case teaching in statistics courses. This article is an attempt to fill that void. It provides a “how-to” starter’s guide for those interested in incorporating case discussions in statistics courses. It includes resources for background reading, tips on setting up a statistics case discussion course, and examples of four specific case discussions involving statistics topics. An illustrative case and instructor’s notes that can be used on the first day of class are provided as well. Because we have had mixed reactions to conducting case discussions online, we believe that the use of case discussion in distance education statistics courses is a fruitful area for experimentation and research. Although our experience is in the business statistics classroom, this article is also applicable to statistics courses in other disciplines.

Estimation efficiency for Markov chain models

In this paper, we evaluate and compare four algorithms for estimating stationary Markov chain models with embedded parameters from aggregate frequency data. By means of factorially designed Monte Carlo simulation experiments, we are able to determine the effects of model characteristics on algorithm accuracy and efficiency. We then present an application, using the best-performing algorithm, for U.S. population migration.

Nonlinear programming solutions to the nonstationary Markov model

A nonstationary Markov process model with embedded explanatory variables offers a means to account for underlying causal factors while retaining unrestrictive assumptions and the predictive ability of a stochastic framework. We find that a direct search algorithm requiring minimal user preparation is a feasible computational procedure for estimating such a model. We compare this method with several others using factorially designed Monte Carlo simulations and find evidence that a small state space and a long time series lead to better algorithmic performance.

Statistical inference in nonstationary Markov models with embedded explanatory variables

In this paper, we develop an operational nonstationary Markov process model for use with macro aggregate frequency data. Independent, time-variant factors assumed to affect the process of interest are embedded in the model. Transition probabilities are estimated indirectly from the coefficients on the embedded variables. We previously concluded that either the Marquardt or the simplex, derivative-free nonlinear programming algorithm could be used to estimate such a model. Here, we propose a test for parameter stationarity. By means of designed simulation experiments for the two-state model, we find that our test has acceptable Type I error probabilities, and that power rises with the degree of departure from the null hypothesis. Both validity and power performance can be improved by longer time records of data and a greater number of entities observed.

Missteps in Multiple Regression Student Projects: Beyond Association-Not-Causation

This article describes common yet subtle errors that students make in self-designed multiple regression projects, based on experiences in a graduate business statistics course. Examples of common errors include estimating algebraic identities, overlooking suppression, and misinterpreting regression coefficients. Advice is given to instructors about helping students anticipate and avoid these common errors; recommended tactics include extensive written guidelines supplemented with in-class active-learning exercises. Several examples using real data are provided. Brief mention is made of incorporating these activities into online courses. Because self-designed student projects require significant effort from students and faculty, anticipating these common errors, and helping students circumvent them, can go a long way to making student projects a more satisfying experience for all.

Resource allocation in high technology firms: Managerial strategies and empirical results

Abstract Two competing theoretical models of strategic allocation decisions are posited and tested. The long-run model hypothesizes that capital expenditures and R&D activities are important determinants of profit in high technology organizations. Alternatively, the short-run model uses marketing expenditures and payments to investors as predictors of profit. A cross-section of 106 high technology firms is used to compare these long-term and short-term strategies. The findings indicate that R&D and investment in capital improvements are important components of profitability in high technology firms.