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Significance testing - a core technique in statistics for hypothesis testing - is introduced in this volume. Mohr first reviews what is meant by sampling and probability …
Understanding Regression Analysis: An Introductory Guide presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical …
This practical guide teaches nonstatisticians how to analyze and interpret loglinear models using the multigraph The Association Graph and the Multigraph for Loglinear Models …
A unique, practical manual for identifying and analyzing item bias in standardized tests. Osterlind discusses five strategies for detecting bias: analysis of variance, transformed …
Author William G. Jacoby focuses on graphical displays that researchers can employ as an integral part of the data analysis process. Such visual depictions are frequently more …
Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When …
Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model …
Aimed at demystifying probability theory, this text provides a brief and non-technical introduction to the subject. Employing few formulas, Rudas uses intuitive but precise …
Which log-linear models can social scientists use to examine categorical variables whose attributes may be logically rank ordered? Ordinal Log-Linear Models presents a technique …
"Nonparametric Statistics is a short and sweet introduction to the five most familiar nonparametric location tests and associated confidence intervals and multiple comparisons. . . …