Predicting incoming enrollment is an ongoing concern for the School District of Philadelphia (SDP) and similar districts with school choice systems, substantial student mobility, or both. Inaccurate predictions can disrupt learning as districts adjust to enrollment fluctuations by reshuffling teachers and students well into the fall semester. This…

A rapidly growing number of algorithms are available to researchers who apply statistical or machine learning methods to answer social science research questions. The unique advantages and limitations of each algorithm are relatively well known, but it is not possible to know in advance which algorithm is best suited for the particular research…

More than half of North Carolina's grade 3 students struggle with reading. The percentage of students scoring below proficient in reading at the end of grade 3 was 55 percent in 2017/18. That percentage has remained largely unchanged, at above 50 percent, since 2013/14, when North Carolina passed its K-3 Read to Achieve literacy act. Read to…

The purpose of this article is to describe effect coding as an alternative quantitative practice for analyzing and interpreting categorical, race-based independent variables in higher education research. Unlike indicator (dummy) codes that imply that one group will be a reference group, effect codes use average responses as a means for…

Financial analysts generally create static formulas for the computation of NPV. When they do so, however, it is not readily apparent how sensitive the value of NPV is to changes in multiple interdependent and interrelated variables. It is the aim of this paper to analyze this variability by employing a dynamic, visually graphic presentation using…

This article describes a bivariate data set that is interesting to students. Indeed, this particular data set, which involves twins and IQ, has sparked more student interest than any other set that I have presented. Specific uses of the data set are presented.

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This ninth installment of "Explorations in Statistics" explores the analysis of ratios and normalized--or standardized--data. As researchers, we compute a ratio--a numerator divided by a denominator--to compute a…

Multiple regression is part of a larger statistical strategy originated by Gauss. The authors raise questions about the theory and suggest some changes that would make room for Mandelbrot and Serendipity.

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

Descripting Statistics provides methodology and tools for user-friendly presentation of random data. Among the summary measures that describe focal tendencies in random data, the mode is given the least amount of attention and it is frequently misinterpreted in many introductory textbooks on statistics. The purpose of the paper is to provide a…

Scholars agree that aggression among children can lead to a host of delinquency issues that can last into adulthood. Research has found that exposure to violence is one of the strongest predictors of aggressive behaviour and the use of violence. Utilizing a mix of qualitative and quantitative methodologies, the article seeks to determine the…

Recently there has been a renewed interest in formative measurement and its role in properly specified models. Formative measurement models are difficult to identify, and hence to estimate and test. Existing solutions to the identification problem are shown to not adequately represent the formative constructs of interest. We propose a new two-step…

This article is designed to give the reader a conceptual, nontechnical overview of estimation and model fit issues in multilevel modeling (MLM). The process of MLM generally involves fitting a series of multilevel models that increase in complexity. When conducting multilevel analyses, it is important to balance the need for complexity and the…

The traditional approach to measuring segregation is based upon descriptive, non-model-based indices. A recently proposed alternative is multilevel modeling. The authors further develop the argument for a multilevel modeling approach by first describing and expanding upon its notable advantages, which include an ability to model segregation at a…