2021 by Michelle Oja, Taft College.
Provides students with a foundation in statistics as used in psychological, sociological, and behavioral research. Students will develop an understanding of research design, the organization of data, measures of central tendency and variability, central tendency theory, descriptive and inferential statistics, parametric and nonparametric tests, and basic test assumptions. The focus includes application of technology for statistical analysis including the interpretation of the relevance of the statistical findings. Applications use data from disciplines including business, social sciences, psychology, life science, health science, and education.
2018 by Garett C. Foster, University of Missouri-St. Louis, David Lane et al, Rice University, Heidi Zimmer, University of Houston.
Cover nearly all of the same material of Gravetter & Walleneau. Does not cover factorial ANOVA.
2018 by Russell A. Poldrack, Stanford University.
This book focuses on understanding the basic ideas of statistical thinking — a systematic way of thinking about how we describe the world and use data make decisions and predictions. Undergraduate Statistics in behvioral science course.
2019 by Danielle Navarro, University of New South Wales.
Covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. Discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.
Unlimited User Ebooks in UML Library: Statistics for Psychology