Digital library
Textbooks, references and open learning resources.
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Introduction to Applied Statistics for Psychology Students
Gordon E. Sarty · University of Saskatchewan
In the contents: 02: Descriptive Statistics - Frequency Data (Counting) · 03: Descriptive Statistics- Central Tendency and Dispersion · 6.04: Robust Statistics
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Applied Statistics for Social Science (19-20)
LibreTexts
In the contents: 1.2: Definitions of Statistics Probability and Key Terms · 02: Descriptive Statistics · 2.1: Prelude to Descriptive Statistics
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Applied Statistics for Social Science
LibreTexts
In the contents: 1.2: Definitions of Statistics, Probability, and Key Terms · 02: Descriptive Statistics · 2.1: Prelude to Descriptive Statistics
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Introduction to Applied Statistics for Psychology Students
Gordon Sarty · University of Saskatchewan · 2022
Introduction to Applied Statistics for Psychology Students, by Gordon E. Sarty (Professor, Department of Psychology, University of Saskatchewan) began as a textbook published in PDF format, in various editions between 2014-2017. The book was written to meet the needs of University of Saskatchewan psychology students at the undergraduate (PSY 233, PSY 234) level. In 2019-2020, funding was provided through the Gwenna Moss Centre for Teaching and Learning, along with technical assistance from the Distance Education Unit, to update and adapt this book, making it more widely available in an easy-to-use and more adaptable digital (Pressbooks) format. The update also made revisions so that the book could be published with a license appropriate for open educational resources (OER). OERs are defined as “teaching, learning, and research resources that reside in the public domain or have been released under an intellectual property license that permits their free use and re-purposing by others” (Hewlett Foundation). This textbook and other OERs like it are openly licensed using a Creative Commons license, and are offered in various digital and e-book formats free of charge. Printed editions of this book can be obtained for a nominal fee through the University of Saskatchewan bookstore.
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Business Statistics
OpenStax · LibreTexts
In the contents: 1.01: Definitions of Statistics Probability and Key Terms · 02: Descriptive Statistics · 2.00: Introduction to Descriptive Statistics
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Applied Probability
Paul Pfeiffer · Rice University
In the contents: 13.03: Simple Random Samples and Statistics · 17.01: Appendix A to Applied Probability- Directory of m-functions and m-procedures · 17.02: Appendix B to Applied Probability- some mathematical aids
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Natural Resources Biometrics
Diane Kiernan · SUNY College of Environmental Science and Forestry
In the contents: 01: Descriptive Statistics and the Normal Distribution · 1.01: Descriptive Statistics
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Introduction to Statistics in the Psychological Sciences
Linda R. Cote, Rupa G. Gordon, Chrislyn E. Randell, Judy Schmitt, and Helena Marvin · LibreTexts
In the contents: 01: Unit 1- Fundamentals of Statistics
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Quantitative Research Methods for Political Science, Public Policy and Public Administration
Jenkins-Smith et al. · University of Oklahoma
The focus of this book is on using quantitative research methods to test hypotheses and build theory in political science, public policy and public administration. It is designed for advanced undergraduate courses, or introductory and intermediate graduate-level courses.
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Basic Statistics Using R for Crime Analysis
Jaeyong Choi · West Chester University
In the contents: 03: Creating a New Variable and Producing Summary Statistics
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Biological Statistics
John H. McDonald · University of Delaware
In the contents: 03: Descriptive Statistics · 3.01: Statistics of Central Tendency · 3.02: Statistics of Dispersion
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Answering Questions with Data - Introductory Statistics for Psychology Students
Matthew J. C. Crump · Brooklyn College of CUNY
In the contents: 01: Why Statistics · 1.01: On the Psychology of Statistics · 1.03: Statistics in Psychology
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An Introduction to Psychological Statistics
Foster et al. · LibreTexts
In the contents: 1.01: What are statistics · 1.02: Why do we study statistics
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Social Data Analysis: Qualitative and Quantitative Approaches
Mikaila Mariel Lemonik Arthur and Roger Clark · Rhode Islange College
This book is meant to help you in your initial attempts to analyze data. In doing so it will introduce you to ways that others have found useful in their attempts to organize data. You might think of it as like a recipe book, a resource that you can refer to as you prepare data for your own consumption and that of others. And, like a recipe book that teaches you to prepare simple dishes, you may find this one pretty exciting.
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Learning Statistics with R - A tutorial for Psychology Students and other Beginners
DJ Navarro · University of New South Wales
In the contents: 01: Why Do We Learn Statistics · 1.01: On the Psychology of Statistics · 1.03: Statistics in Psychology
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Statistics for Research Students
Erich C Fein, John Gilmour, Tayna Machin, and Liam Hendry · University of Southern Queensland
In the contents: 1.02: Descriptive Statistics · 02: Test Statistics p Values Confidence Intervals and Effect Sizes · 09: Nonparametric Statistics
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Mike’s Biostatistics Book
Michael R Dohm · Chaminade University
In the contents: 2.1: Why (Bio)Statistics · 2.3: A brief history of (bio)statistics · 2.4: Experimental Design and rise of statistics in medical research
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A Contemporary Approach to Research and Statistics in Psychology
Klaire Somoray · James Cook University
In the contents: 1.01: What can Statistics do for us · 1.03: Big Ideas in Statistics · 09: Beyond Research and Statistics
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Big Data for Epidemiology: Applied Data Analysis Using National Health Surveys
Tiffany Kindratt · Mavs Open Press · 2022
National data sets provide an avenue for students to practice data analytic skills while also answering meaningful research questions. This open education resource was developed to train future public health professionals how to conduct secondary data analysis of national health surveys using SAS statistical software. SAS software was selected because it is one of the most commonly used software programs used among public health departments and academia. The book includes details on how to analyze public-use data from five common national health surveys, including the National Health Interview Survey (NHIS), Medical Expenditure Panel Survey (MEPS), Health Information National Trends Survey (HINTS), Behavior Risk Factor Surveillance System (BRFSS) and National Health and Nutrition and Examination Survey (NHANES). All datasets and corresponding syntax files are available from the Open ICPSR Data Repository.
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Statistical Thinking for the 21st Century
Russell Poldrack · Russell Poldrack · 2018
Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.