
Significant Statistics
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John Morgan Russell, Virginia Tech University
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Publisher: Virginia Tech Publishing
Language: English
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CC BY-SA
Table of Contents
- Acknowledgements
- Introduction
- About the Author
- Instructor Resources
- Chapter 1: Sampling and Data
- 1.1 Introduction to Statistics
- 1.2 Data Basics
- 1.3 Data Collection and Observational Studies
- 1.4 Designed Experiments
- 1.5 Sampling
- Chapter 1 Wrap-Up
- Chapter 2: Univariate Descriptive Statistics
- 2.1 Descriptive Statistics and Frequency Distributions
- 2.2 Displaying and Describing Categorical Distributions
- 2.3 Displaying Quantitative Distributions
- 2.4 Describing Quantitative Distributions
- 2.5 Measures of Location and Outliers
- 2.6 Measures of Center
- 2.7 Measures of Spread
- Chapter 2 Wrap-Up
- Chapter 3: Bivariate Descriptive Statistics
- 3.1 Introduction to Bivariate Data
- 3.2 Visualizing Bivariate Quantitative Data
- 3.3 Measures of Association
- 3.4 Modeling Linear Relationships
- 3.5 Cautions about Regression
- Chapter 3 Wrap-Up
- Chapter 4: Probability Distributions
- 4.1 Introduction to Probability and Random Variables
- 4.2 Discrete Random Variables
- 4.3 The Binomial Distribution
- 4.4 Continuous Random Variables
- 4.5 The Normal Distribution
- 4.6 The Normal Approximation to the Binomial
- Chapter 4 Wrap-Up
- Chapter 5: Foundations of Inference
- 5.1 Point Estimation and Sampling Distributions
- 5.2 The Sampling Distribution of the Sample Mean (Central Limit Theorem)
- 5.3 Introduction to Confidence Intervals
- 5.4 The Behavior of Confidence Intervals
- 5.5 Introduction to Hypothesis Tests
- 5.6 Hypothesis Tests in Depth
- Chapter 5 Wrap-Up
- Chapter 6: Inference for One Sample
- 6.1 The Sampling Distribution of the Sample Mean (t)
- 6.2 Inference for the Mean in Practice
- 6.3 The Sampling Distribution of the Sample Proportion
- 6.4 Inference for a Proportion
- 6.5 Behavior of Confidence Intervals for a Proportion
- Chapter 6 Wrap-Up
- Chapter 7: Inference for Two Samples
- 7.1 Inference for Two Dependent Samples (Matched Pairs)
- 7.2 Inference for Two Independent Sample Means
- 7.3 Inference for Two-Sample Proportions
- Chapter 7 Wrap-Up
- Chapter 1 Extra Practice
- Chapter 2 Extra Practice
- Chapter 3 Extra Practice
- Chapter 4 Extra Practice
- Chapter 5 Extra Practice
- Chapter 6 Extra Practice
- Chapter 7 Extra Practice
- Glossary
- Tables
- Version Notes
Ancillary Material
Submit ancillary resourceAbout the Book
Significant Statistics: An Introduction to Statistics is intended for students enrolled in a one-semester introduction to statistics course 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.
Significant Statistics: An Introduction to Statistics was adapted from content published by OpenStax including Introductory Statistics, OpenIntro Statistics, and Introductory Statistics for the Life and Biomedical Sciences. John Morgan Russell reorganized the existing content and added new content where necessary.
Instructors reviewing, adopting, or adapting this textbook: please help us understand your use by filling out this form: https://bit.ly/stat-interest.
About the Contributors
Author
John Morgan Russell teaches various introductory statistics courses at Virginia Tech, and previously taught at George Mason University and Old Dominion University. He earned a BS in Mathematics from Christopher Newport University, an MS in Statistical Science from George Mason University, and an Ed.S. in Instructional design and Technology from Virginia Tech. His interests include statistics education, instructional design, and open educational resources.