The Persistence Of Traditional Gender Stereotypes: Evidence From The Distribution Of Academic Honors At A Female-Majority University

A shift from male-majority to female-majority university campuses has opened up new areas for research on gender bias, stereotypes, and discrimination. At one large state university on the west coast, there were more female than male graduates in Spring, 2008 in 7 out of 8 colleges, including the traditionally male-majority areas of business and science.  Relative probabilities for men and women of receiving honors in each major field of study at this school, compared to national data of gender breakdowns by field in 1980, showed that men and women were still relatively more likely to receive honors in fields that were traditionally male and female, respectively. Findings also cast doubt upon Kanter’s tokenism hypothesis. Curiously, it was traditionally female, not male, fields that had the highest levels of gender inequity, though gender inequity overall may be on a decline. More research is needed to identify why this difference between gender and honors still exists. Universities should also be aware of the continuing potential for subtle gender discrimination, even in fields where equal numbers of men and women participate

What’s Good in Theory May Be Flawed in Practice: Potential Legal Consequences of Poor Implementation of a Theoretical Sample

This article discusses the problems with the use of statistical sampling in litigation. Sample-based research is increasingly used in a diverse array of cases including products liability, antitrust, intellectual property, and criminal law. Sample-based research provides objective evidence upon which decisions, damages, and liability may rest. Despite its importance, however, statistical evidence is often misused and misunderstood by attorneys unfamiliar with the underlying form of analysis. This article explores common errors when using litigative samples, comments upon best practices for the use in law of sample-based research, and demonstrates the importance of sound statistical sampling and data collection in a recent case

ACTIVE SUPPRESSION AS A POSSIBLE MECHANISM OF TOLERANCE IN TETRAPARENTAL MICE

Previous work has indicated that tetraparental mice, chimeric since the eight-cell stage because of embryo fusion using histoincompatible strain combinations, possess autospecific immune cells and blocking antibodies. Although this phenomenon has been demonstrated in vitro, it may have relevance to the self-tolerance shown by these mice in vivo. The experiments described here indicate that spleen cells from tetraparental mice can block mixed lymphocyte reactions between the two parental cell types, but not between unrelated strains. Furthermore, this suppressive ability is not affected by an otherwise effective treatment of the tetraparental spleen cells with anti-θ antibody and complement. The in vitro experimental system elaborated here should help to characterize the cell type responsible for the suppression

Misleading Betas: An Educational Example

The dual-beta model is a generalization of the CAPM model. In the dual-beta model, separate beta estimates are provided for up-market and down-market days. This paper uses the historical “Anscombe quartet” results which illustrated how very different datasets can produce the same regression coefficients to motivate a discussion of the dual-beta model. Using data from 39 mutual funds, it is shown how very different dual-beta models can lead to the same CAPM beta estimates, much like the Anscombe quartet scenarios

Improved Margin Of Error Estimates For Proportions In Business: An Educational Example

This paper presents the Agresti & Coull “Adjusted Wald” method for computing confidence intervals and margins of error for common proportion estimates.  The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small sample situations.  The proposed method may have particular applications to focus group analysis, industry benchmarking, and destructive testing sampling.  The paper discusses a computational strategy and several comparison examples

Statistical Analysis Of A Class: Monte Carlo And Multiple Imputation Spreadsheet Methods For Estimation And Extrapolation

The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems.  However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are not immersed in the realm of mathematics or science.  This paper introduces these Monte Carlo methods for the non-mathematician and business student, providing examples where the Monte Carlo method is applied when only small samples are available.  Statistical analysis and statistically sound extrapolation of sample characteristics to the larger class population can be facilitated by applying Monte Carlo methods and the related concept of multiple imputation, which is also explained.  Appendices provide step-by-step instructions for using two popular spreadsheet add-ins to run Monte Carlo based analysis

Finding The Beta For A Portfolio Isn't Obvious: An Educational Example

When a portfolio is not actively managed to maintain a fixed investment percentage in each asset but rather maintains a fixed number of shares for each asset, the portfolio weights will change over time because the market returns of the different assets will not be the same.  Consequently, portfolio betas computed as a linear combination of asset betas, which is the usual practice, will be different from betas computed using regression techniques on portfolio returns as is done when evaluating individual assets and mutual funds.  The alternative approaches can result in quite different beta statistics and, consequently, inconsistent decisions depending on which method is used.&nbsp

An Overview Of Fiduciary Standards And Suitability For Financial Planning Students

Financial planning is an interdisciplinary field including finance and business law topics. Consequently, standard pedagogical resources often omit topics that fall between these fields. To address a key gap in educational materials for financial planning students and faculty, this article reviews recent regulatory developments for financial planning students, including strengthened fiduciary standards and FINRA suitability requirements. The discussion introduces FINRA 2090, FINRA 2111, the Uniform Prudent Investor Act, and other widely adopted fiduciary-oriented model laws. The article concludes with a discussion of implications for financial planning professors and students

An Introduction To Cost-Of-Living Adjustments In Public Retirement Plans: Details Matter

While financial planning students are expected to be able to understand client retirement plans, subtle differences in cost-of-living adjustments can have major impact on the success of client retirement plans. This teaching note compares the cost-of-living adjustments in the largest government sponsored retirement systems and a hypothetical traditional privately sponsored plan.  Using a Monte Carlo simulation, we estimate the impact on retirement experience from the different COLAs.  These differences are large, with differing protection from future inflation and differing risk for running out of money during retirement. This teaching note will help instructors address Certified Financial Planner (CFP) Board Learning Outcome G.52 “Retirement Needs Analysis”.   The material may also be used in economics, human resources, public administration, and other classes addressing policy aspects of retirement plans