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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
Snell, Joel C.; Marsh, Mitchell – Education, 2012
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.
Descriptors: Multiple Regression Analysis, Statistics, Measurement, Multivariate Analysis
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
Strand, Kenneth H. – Online Submission, 2000
This paper contains information concerning the following: 1. An overview of multivariate analysis of variance, and discriminant (DA) and canonical (CA) analyses. 2. An introduction to specification and measurement errors, and collinearity. 3. The sparsity of information concerning specification and measurement errors and collinearity as they…
Descriptors: Multivariate Analysis, Multiple Regression Analysis, Discriminant Analysis, Error of Measurement

Kerwin, Mary Louise E.; And Others – Counseling Psychologist, 1987
Describes the strengths and weaknesses of a new type of multivariate technique, covariance structure analysis (LISREL). Provides a detailed example which shows how the use of covariance structure analysis can improve research sophistication and theory development in counseling psychology. (Author/ABB)
Descriptors: Counseling, Multiple Regression Analysis, Multivariate Analysis, Psychology
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

Sullins, Walter L. – Contemporary Education, 1983
This paper comments on the impact of computers on statistical analysis and presents a concise, nontechnical overview of five statistical methods now being applied in educational research. Appropriate uses of these techniques are pointed out, along with dangers concerning misapplications. (PP)
Descriptors: Comparative Analysis, Computer Programs, Discriminant Analysis, Educational Research

Ewert, Alan; Sibthorp, Jim – Journal of Experiential Education, 2000
Multivariate analytic techniques offer useful research methods that permit the experiential educator to test theoretical models, analyze the effects of several variables acting together, and predict the effects of one set of variables upon another set of variables. Several of these techniques are discussed, including analysis of variance, multiple…
Descriptors: Adventure Education, Analysis of Covariance, Analysis of Variance, Educational Research

Maeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics