Digital library
Textbooks, references and open learning resources.
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An Intuitive, Interactive, Introduction to Biostatistics
Caitlin Ward; Collin Nolte · University of Iowa · 2023
"An Intuitive, Interactive Introduction to Biostatistics" is an introductory statistics textbook oriented towards towards undergraduate students in the health sciences. While covering the breadth of material typically presented in a first semester statistics course, including introductions to probability and distributions, study design, CLT, hypothesis testing, and inference, IIIB distinguishes itself with its focus on cultivating student intuition through the use of guided questions and interactive simulation-based applets. Written in R, this open-source text has been created with customizability in mind, offering instructors maximal flexibility in arranging and modifying the content.
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Mostly Harmless Elementary Statistics
Rachel Webb · Portland State University Library · 2023
This text is for an introductory level probability and statistics course with an intermediate algebra prerequisite. The focus of the text follows the American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE). Software examples provided for Microsoft Excel, TI-84 & TI-89 calculators. Students new to statistics are sure to benefit from this ADA accessible and relevant textbook. The examples are current and resonate with everyday life. The casual narrative style, has a conversational tone to provide an inclusive and easy to read format for students.
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Intermediate Statistics with R
Mark Greenwood · Montana State University · 2021
Introductory statistics courses prepare students to think statistically but cover relatively few statistical methods. Building on the basic statistical thinking emphasized in an introductory course, a second course in statistics at the undergraduate level can explore a large number of statistical methods. This text covers more advanced graphical summaries, One-Way ANOVA with pair-wise comparisons, Two-Way ANOVA, Chi-square testing, and simple and multiple linear regression models. Models with interactions are discussed in the Two-Way ANOVA and multiple linear regression setting with categorical explanatory variables. Randomization-based inferences are used to introduce new parametric distributions and to enhance understanding of what evidence against the null hypothesis “looks like”. Throughout, the use of the statistical software R via Rstudio is emphasized with all useful code and data sets provided within the text. This is Version 3.0 of the book.
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Learning Statistics with R: A tutorial for psychology students and other beginners
Danielle Navarro · Danielle Navarro · 2018
Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book 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.
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Introduction to Statistics
David Lane · David Lane · 2003
Introduction to Statistics is a resource for learning and teaching introductory statistics. This work is in the public domain. Therefore, it can be copied and reproduced without limitation. However, we would appreciate a citation where possible. Please cite as: Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University. Instructor's manual, PowerPoint Slides, and additional questions are available.
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Statistical Inference For Everyone
Brian Blais · Brian Blais · 2017
This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester of such a course. It is freely available under the Creative Commons License, and includes a software library in Python for making some of the calculations and visualizations easier.
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Quantway Core
Carnegie Math Pathways · WestEd
In the contents: 2.07: Making Good Decisions with Good Statistics
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Biology for an Informed World
Trevor Rivers · University of Kansas
In the contents: 1.01: What is different about this approach to Introductory Biology · 1.05: Descriptive Statistics and Graphing
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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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Statistics: Open for Everyone
Christina R. Peter · Los Angeles Valley College
In the contents: 01: Introduction to Statistics · 1.01: What is Statistics · 1.02: Tenets of Statistics
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MA336:Statistics
Fei Yi · Queensborough Community College
In the contents: 02: Descriptive Statistics
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Clinical Chemistry - Theory, Analysis, Correlation
Lawrence Kaplan & Amadeo Pesce · New York University & University of Cincinnati
In the contents: 1.01: Introductory Principles · 1.16: Statistics and Reference Ranges
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Introduction to Statistics with R
Edward Chi · Cerritos College
In the contents: 1.1.02: Dealing with Statistics Anxiety · 1.1.03: What Can Statistics Do for Us · 1.1.04: The Big Ideas of Statistics
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CHEM310L - Physical Chemistry I Lab Manual
Kathryn Haas · Duke University
In the contents: 1.02: Introductory Details · 3.03: Estimating and Reporting Error (Statistics Propogation and Rounding) · 9.9.02: Estimating and Reporting Error (Statistics Propogation and Rounding)
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Physics 9HC: Introduction to Waves, Physical Optics, and Quantum Theory
Tom Weideman · University of California, Davis
In the contents: 8.4: Statistics of Identical Particles
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Introduction to Statistics (MATH 025, CID: 110)
Lynn Mann · Coalinga College
In the contents: 01: Sampling and Descriptive Statistics · 1.02: Definitions of Statistics Probability and Key Terms · 1.06: Prelude to Descriptive Statistics
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BIO Majors 4A+4B Lab Manual
Darcy Ernst, May Chen, Katie Foltz, and Bridget Greuel · Evergreen Valley College
In the contents: 36: Appendix B - Brief Introduction to Statistics · 36.01: Reading - Descriptive Statistics and Graphing
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Analytical Chemistry 2.1
David Harvey · DePauw University
The introductory course in analytical chemistry is the ideal place in the undergraduate chemistry curriculum for exploring topics such as experimental design, sampling, calibration strategies, standardization, optimization, statistics, and the validation of experimental results. Analytical methods come and go, but best practices for designing and validating analytical methods are universal.
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Lies, Damned Lies, or Statistics - How to Tell the Truth with Statistics
Jonathan A. Poritz · Colorado State University – Pueblo
In the contents: 01: One-Variable Statistics - Basics · 02: Bi-variate Statistics - Basics · 06: Inferential Statistics