/ims

📚 Introduction to Modern Statistics - A college-level open-source textbook with a modern approach highlighting multivariable relationships and simulation-based inference.

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Introduction to Modern Statistics

Where did Introduction to Statistics with Randomization and Simulation go?

As we're working on the 2nd edition of this book, we realized that we weren't too enamoured by the name, and decided to rename the book to "Introduction to Modern Statistics" to better reflect the content covered in the book, which features simulation-based inference but also many non-inference topics!

If you're looking for the source files for the 1st edition of OpenIntro - Introduction to Statistics with Randomization and Simulation, please download the zipped release here.

What's planned for Introduction to Modern Statistics?

Some restructuring, some reordering, and some new content with better treatment of randomization and simulation throughout the book.

Each section comes with exercises as well as chapter level exercises in the last (review) section of each chapter. The review section also includes interactive R tutorials and labs.

Preliminary edition

Preliminary edition of Introduction to Modern Statistics is now complete and can be found at https://openintro-ims.netlify.app.

Chp 1. Getting started with data

Complete

  • Case study
  • Data basics
  • Sampling principles and strategies
  • Experiments
  • Chapter review

Chp 2. Summarizing and visualizing data

Complete

  • Exploring numerical data
  • Exploring categorical data
  • Effective data visualization
  • Case study
  • Chapter review

Chp 3. Introduction to linear models

Complete

  • Fitting a line, residuals, and correlation
  • Least squares regression
  • Outliers in linear regression

Chp 4. Multivariable and logistic models

Complete

  • Regression with multiple predictors
  • Model selection
  • Logistic regression

Chp 5. Introduction to statistical inference

Complete, exercises need to be added

  • Randomization tests
  • Bootstrap confidence intervals
  • Mathematical models

Chp 6. Inference for categorical responses

Complete, exercises need to be added

  • One proportion

    • Bootstrap test
    • Bootstrap confidence interval
    • Mathematical model

  • Difference of two proportions

    • Randomization test
    • Bootstrap confidence interval
    • Mathematical model

  • Independence in two way tables

    • Randomization test
    • Bootstrap confidence interval
    • Mathematical model

Chp 7. Inference for numerical responses

Complete, exercises need to be added

  • One mean

    • Bootstrap confidence interval
    • Mathematical model

  • Difference of two means

    • Randomization test
    • Bootstrap confidence interval
    • Mathematical model

  • Paired differences

    • Randomization test
    • Bootstrap confidence interval
    • Mathematical model

  • Comparing many means

    • Randomization test
    • Mathematical model

Chp 8. Inference for regression

Complete, exercises need to be added

  • Inference for linear regression

    • Randomization test
    • Bootstrap confidence interval
    • Mathematical model

  • Checking model assumptions

  • Inference for multiple regression

  • Inference for logistic regression

First edition

THIS IS A WORK IN PROGRESS!!!

We're currently in the process of finalizing the first edition of Introduction to Modern Statistics. It will be available Summer 2021. In the meantime, you can follow along with updates to the first edition here however we do not recommend using the in progress version for teaching while it's being updated as we might move around sections content and exercises, which might be unexpected for you and your students.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.