Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection ("type I errors") is…

The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

In a provocative and influential paper, Jesse Rothstein (2010) finds that standard value added models (VAMs) suggest implausible future teacher effects on past student achievement, a finding that obviously cannot be viewed as causal. This is the basis of a falsification test (the Rothstein falsification test) that appears to indicate bias in VAM…

In recent years, there has been some dispute over the appropriate way to model decision making in professional sports leagues. In particular, Szymanski and Kesenne (2004) argue that formulating the decision-making problem in a noncooperative game leads to radically different conclusions about the nature of competition in sports leagues. The author…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

An important part of the analysis of the expected effects of institutional closure is estimation of redistribution of students attending the closed school. How coefficient estimates from models of enrollment demand can be used to predict the alternative attendance choices of students enrolled at the closed school is discussed. (Author/MLW)