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Keefer, Quinn A. W. – Journal of Economic Education, 2023
An alternative approach for introducing instrumental variables in econometrics courses is presented in this article. The method is based on the ordinary least squares omitted variable bias formula. The intuition for the approach capitalizes on students' understanding and intuition of omitted variables. Thus, if students understand omitted variable…
Descriptors: Least Squares Statistics, Economics, Economics Education, Computation
Murray, Lori L.; Wilson, John G. – Decision Sciences Journal of Innovative Education, 2021
Summary statistics and data visualizations are often used to explore data and draw preliminary conclusions. Although valuable, these tools do not always reveal the underlying patterns and trends in the data and can sometimes be misleading. We describe an approach for teaching the need for more advanced statistical analysis using multiple linear…
Descriptors: Statistics Education, Teaching Methods, Multiple Regression Analysis, Multivariate Analysis
Astivia, Oscar L. Olvera; Zumbo, Bruno D. – Practical Assessment, Research & Evaluation, 2019
Within psychology and the social sciences, Ordinary Least Squares (OLS) regression is one of the most popular techniques for data analysis. In order to ensure the inferences from the use of this method are appropriate, several assumptions must be satisfied, including the one of constant error variance (i.e. homoskedasticity). Most of the training…
Descriptors: Multiple Regression Analysis, Least Squares Statistics, Statistical Analysis, Error of Measurement
Bodner, Todd E. – Journal of Educational and Behavioral Statistics, 2016
This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…
Descriptors: Graphs, Multiple Regression Analysis, Predictor Variables, Correlation
Johnson, Roger W. – Journal of Statistics and Data Science Education, 2021
Percentage of body fat, age, weight, height, and 14 circumference measurements (e.g., waist) are given for 184 women aged 18-25. Body fat, one measure of health, was accurately determined by an underwater weighing technique which requires special equipment and training of the individuals conducting the process. Modeling body fat percentage using…
Descriptors: Body Composition, Statistics Education, Teaching Methods, Age Differences
El-Majali, Basel Abdel Wahab – Journal of Education and Practice, 2016
In this article, the Higher Council of Youth in Jordan seeks to develop its services, to participate actively in King Abdullah II award for excellence and transparency, to promote the concepts of quality in all its activities and to take advantage of modern technology in the output of its programs and activities. This study considered as one of…
Descriptors: Foreign Countries, Organizational Culture, Organizational Climate, Public Agencies
Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya – International Educational Data Mining Society, 2016
The past few years has seen the rapid growth of data mining approaches for the analysis of data obtained from Massive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a student may achieve on a given grade-related assessment based on information, considered as prior performance or prior…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
Lynch, David; Smith, Richard; Provost, Steven; Madden, Jake – Journal of Educational Administration, 2016
Purpose: This paper argues that in a well-organised school with strong leadership and vision coupled with a concerted effort to improve the teaching performance of each teacher, student achievement can be enhanced. The purpose of this paper is to demonstrate that while macro-effect sizes such as "whole of school" metrics are useful for…
Descriptors: Foreign Countries, Teacher Effectiveness, Academic Achievement, Data Interpretation