Includes bibliographical references (pages 1126-1133) and index.
Review of basic concepts -- Basic statistics, sampling error, and confidence intervals -- Statistical significant testing -- Preliminary data screening -- Comparing group means using the independent samples t test -- One-way between-subjects analysis of variance -- Bivariate pearson correlation -- Alternative correlation coefficients -- Bivariate regression -- Adding a third variable: Preliminary exploratory analyses -- Multiple regression with two predictor variables -- Dummy predictor variables in multiple regression -- Factorial analysis of variance -- Multiple regression with more than two predictors -- Moderation: Tests for interaction in multiple regression -- Mediation -- Analysis of covariance -- Discriminant analysis -- Multivariate analysis of variance -- Principal components and factor analysis -- Reliability, validity, and multiple-item scales -- Analysis of repeated measures -- Binary logistic regression.
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Applied statistics : from bivariate through multivariate techniques, Second Edition, provides a clear introduction to widely used topics in bivariate and multivariate statistics including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic refression. Author, Rebecca M Warner, uses an applied approach that does not require formal mathematics; equations are accompanied by verbal explanations, and students are asked to think about the meaning of the equation.