Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 6 |
Descriptor
Source
Author
Publication Type
Reports - Descriptive | 11 |
Journal Articles | 9 |
Books | 1 |
Guides - General | 1 |
Reports - Research | 1 |
Education Level
Higher Education | 1 |
Audience
Researchers | 1 |
Location
India | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
Karanam, Saraschandra; van Oostendorp, Herre; Indurkhya, Bipin – Behaviour & Information Technology, 2012
CoLiDeS + Pic is a cognitive model of web-navigation that incorporates semantic information from pictures into CoLiDeS. In our earlier research, we have demonstrated that by incorporating semantic information from pictures, CoLiDeS + Pic can predict the hyperlinks on the shortest path more frequently, and also with greater information scent,…
Descriptors: Semantics, Hypermedia, Semiotics, Visual Stimuli
Zhang, Zhiyong; McArdle, John J.; Wang, Lijuan; Hamagami, Fumiaki – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Bayesian methods are becoming very popular despite some practical difficulties in implementation. To assist in the practical application of Bayesian methods, we show how to implement Bayesian analysis with WinBUGS as part of a standard set of SAS routines. This implementation procedure is first illustrated by fitting a multiple regression model…
Descriptors: Bayesian Statistics, Computer Software, Monte Carlo Methods, Multiple Regression Analysis
Hyde, Hartley – Australian Mathematics Teacher, 2008
When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…
Descriptors: Computer Software, Multiple Regression Analysis, Mathematics Instruction, Spreadsheets
Strang, Kenneth David – Practical Assessment, Research & Evaluation, 2009
This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…
Descriptors: Multicultural Education, Computer Software, Multiple Regression Analysis, Multidimensional Scaling
Aguinis, Herman; Pierce, Charles A. – Applied Psychological Measurement, 2006
The computation and reporting of effect size estimates is becoming the norm in many journals in psychology and related disciplines. Despite the increased importance of effect sizes, researchers may not report them or may report inaccurate values because of a lack of appropriate computational tools. For instance, Pierce, Block, and Aguinis (2004)…
Descriptors: Effect Size, Multiple Regression Analysis, Predictor Variables, Error of Measurement
Algina, James; Olejnik, Stephen – Multivariate Behavioral Research, 2003
Tables for selecting sample size in correlation studies are presented. Some of the tables allow selection of sample size so that r (or r[squared], depending on the statistic the researcher plans to interpret) will be within a target interval around the population parameter with probability 0.95. The intervals are [plus or minus] 0.05, [plus or…
Descriptors: Probability, Intervals, Sample Size, Multiple Regression Analysis

Shelton, Fred Ames – Computers and Education, 1987
Discusses the use and interpretation of multiple regression analysis with computer programs and presents a flow chart of the process. A general explanation of the flow chart is provided, followed by an example showing the development of a linear equation which could be used in estimating manufacturing overhead cost. (Author/LRW)
Descriptors: Computer Software, Cost Estimates, Flow Charts, Graphs
Muijs, Daniel – SAGE Publications, 2004
This book looks at quantitative research methods in education. The book is structured to start with chapters on conceptual issues and designing quantitative research studies before going on to data analysis. While each chapter can be studied separately, a better understanding will be reached by reading the book sequentially. This book is intended…
Descriptors: Multivariate Analysis, Multiple Regression Analysis, Correlation, Educational Research

Fielding, Alan H. – Journal of Biological Education, 1988
Described is a method for discriminant analysis which uses the multiple regression facilities offered by many microcomputer statistical packages. This method is illustrated with an ecological example using the MICROTAB statistical package on a BBC microcomputer. Compares these results with an analysis of the same data using SPSS X. (Author/CW)
Descriptors: Biological Sciences, College Science, Computer Software, Computer Uses in Education
Klass, Patricia Harrington – 1988
The study provides: (1) a rationale for using microcomputer spreadsheet programs as teaching tools in applied statistics courses; (2) examples of one spreadsheet template--Analysis of Variance; (3) corresponding workbook exercises for the ANOVA template; and (4) results and discussion of how the exercises are used in an introductory statistics…
Descriptors: College Mathematics, Computer Assisted Instruction, Computer Software, Computer Uses in Education