Introductory Statistics with Randomization and Simulation offers a novel introduction to statistics at the college level. Extra benefits of Introductory Statistics with Randomization and Simulation vs the expensive alternatives:
- Every student can access the textbook, even before the course starts, for free.
- Students have forever access to the textbook PDF.
- We offer a variety of free supplemental resources, including videos and software labs, on openintro.org.
A new book, Introduction to Modern Statistics, 2nd Edition (IMS is available on the web, as a PDF, and in paperback), represents the evolution of Introductory Statistics with Randomization and Simulation (ISRS). For those who are considering adopting Introductory Statistics with Randomization and Simulation, we recommend Introduction to Modern Statistics instead.
Conditions of Use
This book is licensed under a Creative Commons License (CC BY-SA). You can download the ebook Introductory Statistics with Randomization and Simulation for free.
- Title
- Introductory Statistics with Randomization and Simulation
- Publisher
- OpenIntro
- Author(s)
- Christopher D Barr, David M Diez, Mine Çetinkaya-Rundel
- Published
- 2020-12-29
- Edition
- 1
- Format
- eBook (pdf, epub, mobi)
- Pages
- 354
- Language
- English
- ISBN-10
- 1500576697
- ISBN-13
- 9781500576691
- License
- CC BY-SA
- Book Homepage
- Free eBook, Errata, Code, Solutions, etc.
Introduction to data Case study Data basics Overview of data collection principles Observational studies and sampling strategies Experiments Examining numerical data Considering categorical data Exercises Foundation for inference Randomization case study: gender discrimination Randomization case study: opportunity cost Hypothesis testing Simulation case studies Central Limit Theorem Normal distribution Applying the normal model Confidence intervals Exercises Inference for categorical data Inference for a single proportion Difference of two proportions Testing for goodness of fit using chi-square (special topic) Testing for independence in two-way tables (special topic) Exercises Inference for numerical data One-sample means with the t distribution Paired data Difference of two means Comparing many means with ANOVA (special topic) Bootstrapping to study the standard deviation Exercises Introduction to linear regression Line fitting, residuals, and correlation Fitting a line by least squares regression Types of outliers in linear regression Inference for linear regression Exercises Multiple and logistic regression Introduction to multiple regression Model selection Checking model assumptions using graphs Logistic regression Exercises Probability Defining probability Conditional probability Random variables End of chapter exercise solutions Distribution tables Normal Probability Table t Distribution Table Chi-Square Probability Table
