Propensity score methods account for selection bias in observational studies. However, the consistency of the propensity score estimators strongly depends on a correct specification of the propensity score model. Logistic regression and, with increasing popularity, machine learning tools are used to estimate propensity scores. We introduce a…

In the paper a software solution is presented for the generation of instances of exercises. The focus is on education in mathematics but the approach can be adopted in other fields such as computer science and natural science. The present solution uses the R environment for the generation process and LaTeX for the content presentation. In the…

This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…

As literature has reported, it is usual that university students in statistics courses, and even statistics teachers, interpret the confidence level associated with a confidence interval as the probability that the parameter value will be between the lower and upper interval limits. To confront this misconception, class activities have been…

Repeating an item in a list benefits recall performance, and this benefit increases when the repetitions are spaced apart (Madigan, 1969; Melton, 1970). Retrieved context theory incorporates 2 mechanisms that account for these effects: contextual variability and study-phase retrieval. Specifically, if an item presented at position "i" is…

Test-retest studies for assessing stability and change are widely used in different domains and allow improved or additional individual estimates of interest to be obtained. However, if these estimates are to be validly interpreted the responses given at Time-2 must be free of retest effects, and the fulfilment of this assumption must be…

The unexpectedness of the birthday problem has long been used by teachers of statistics in discussing basic probability calculation. An activity is described that engages students in understanding probability and sampling using the popular Facebook social networking site. (Contains 2 figures and 1 table.)

In a previous gaze-contingent boundary experiment, Angele and Rayner (2013) found that readers are likely to skip a word that appears to be the definite article "the" even when syntactic constraints do not allow for articles to occur in that position. In the present study, we investigated whether the word frequency of the preview of a…

Individuals can partly recreate the "wisdom of crowds" within their own minds by combining nonredundant estimates they themselves have generated. Herzog and Hertwig (2009) showed that this accuracy gain could be boosted by urging people to actively think differently when generating a 2nd estimate ("dialectical bootstrapping").…

The Traveling Salesperson Problem (TSP) is a computationally difficult combinatorial optimization problem. In spite of its relative difficulty, human solvers are able to generate close-to-optimal solutions in a close-to-linear time frame, and it has been suggested that this is due to the visual system's inherent sensitivity to certain geometric…

Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least…

Estimation problems associated with the correlated-trait correlated-method (CTCM) parameterization of a multitrait-multimethod (MTMM) matrix are widely documented: the model often fails to converge; even when convergence is achieved, one or more of the parameter estimates are outside the admissible parameter space. In this study, the authors…

Although Bayesian methodology has become a powerful approach for describing uncertainty, it has largely been avoided in undergraduate statistics education. Here we demonstrate that one can present Bayes' Rule in the classroom through a hypothetical, yet realistic, legal scenario designed to spur the interests of students in introductory- and…

This paper develops a series of models for optimal tuition pricing for private colleges and universities. The university is assumed to be a profit maximizing, price discriminating monopolist. The enrollment decision of student's is stochastic in nature. The university offers an effective tuition rate, comprised of stipulated tuition less financial…

The paper discusses the interaction between intuitive biases of probabilistic thinking and mathematical knowledge. It would appear that students may answer numerical problems correctly but falter on simple descriptive solutions. Students appear to relinquish formal knowledge for simpler heuristics when attempting to describe the outcome of an…