Descriptive statistics; probability; discrete and continuous (including the binomial, normal and T) distributions; sampling distributions; interval estimation; hypothesis testing; linear regression and correlation.

Introductory Statistics follows scope and sequence requirements of a one-semester introduction to …

Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs.

Access also available here: https://openstax.org/details/books/introductory-statistics

Table of Contents Sampling and Data Descriptive Statistics Probability Topics Discrete Random Variables Continuous Random Variables The Normal Distribution The Central Limit Theorem Confidence Intervals Hypothesis Testing with One Sample Hypothesis Testing with Two Samples The Chi-Square Distribution Linear Regression and Correlation F Distribution and One-Way ANOVA

We hope readers will take away three ideas from this book in …

We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods.

(1) Statistics is an applied field with a wide range of practical applications.

(2) You don't have to be a math guru to learn from interesting, real data.

(3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world.

Reviews available here: https://open.umn.edu/opentextbooks/textbooks/introductory-statistics-with-randomization-and-simulation-first-edition

Learning Statistics with R covers the contents of an introductory statistics class, …

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.

This text is for an introductory level probability and statistics course with …

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. A formula packet and pdf version of the text are available on the website http://mostlyharmlessstatistics.com. Students new to probability and statistics are sure to benefit from this fully ADA accessible and relevant textbook. The examples resonate with everyday life, the text is approachable, and has a conversational tone to provide an inclusive and easy to read format for students.

able of Contents Chapter 1 Introduction to Data Chapter 2 Organizing Data Chapter 3 Descriptive Statistics Chapter 4 Probability Chapter 5 Discrete Probability Distributions Chapter 6 Continuous Probability Distributions Chapter 7 Confidence Intervals for One Population Chapter 8 Hypothesis Tests for One Population Chapter 9 Hypothesis Tests & Confidence Intervals for Two Populations Chapter 10 Chi-Square Tests Chapter 11 Analysis of Variance Chapter 12 Correlation and Regression Chapter 12 Formulas Chapter 12 Exercises Chapter 13 Nonparametric Tests

PowerPoint Slides to accompany Chapter 12 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 12 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 1 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 1 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 2 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 2 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 3 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 3 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 4 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 4 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 6 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 6 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 7 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 7 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 8 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 8 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

PowerPoint Slides to accompany Chapter 9 of OpenStax Statistics textbook. Prepared by …

PowerPoint Slides to accompany Chapter 9 of OpenStax Statistics textbook. Prepared by River Parishes Community College (Jared Eusea, Assistant Professor of Mathematics, and Ginny Bradley, Instructor of Mathematics) for OpenStax Statistics textbook under a Creative Commons Attribution-ShareAlike 4.0 International License. Date provided: July 2019.

Significant Statistics: An Introduction to Statistics was adapted and original content added …

Significant Statistics: An Introduction to Statistics was adapted and original content added by John Morgan Russell. It is adapted from content published by OpenStax Introductory Statistics, OpenIntro Statistics, and Introductory Statistics for the Life and Biomedical Sciences.

Significant Statistics: An Introduction to Statistics is intended for the one-semester introduction to statistics course for students who are not mathematics or engineering majors. It focuses on the interpretation of statistical results, especially in real world settings, and assumes that students have an understanding of intermediate algebra. In addition to end of section practice and homework sets, examples of each topic are explained step-by-step throughout the text and followed by a 'Your Turn' problem that is designed as extra practice for students.

Instructors reviewing, adopting, or adapting this textbook, please help us understand your use by filling out this form: https://bit.ly/stat-interest.

Table of Contents:

Chapter 1: Sampling and Data Chapter 2: Descriptive Statistics Chapter 3: Basics of Probability Chapter 4: Discrete Random Variables Chapter 5: Continuous Random Variables Chapter 6: Foundations of Inference Chapter 7: Inference for One Sample Chapter 8: Inference for Two Samples Chapter 9: Simple Linear Regression Class Group Activities

Statistical thinking is a way of understanding a complex world by describing …

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.

Table of Contents 1 Introduction 2 Working with data 3 Probability 4 Summarizing data 5 Fitting models to data 6 Data Visualization 7 Sampling 8 Resampling and simulation 9 Hypothesis testing 10 Confidence intervals, effect sizes, and statistical power 11 Bayesian statistics 12 Modeling categorical relationships 13 Modeling continuous relationships 14 The General Linear Model 15 Comparing means 16 The process of statistical modeling: A practical example 17 Doing reproducible research

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