Statistical Thinking
eBook - PDF

Statistical Thinking

Analyzing Data in an Uncertain World

  1. 248 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Statistical Thinking

Analyzing Data in an Uncertain World

About this book

An essential introduction to statistics for students of psychology and the social sciences

Statistical thinking is increasingly essential to understanding our complex world and making informed decisions based on uncertain data. This incisive undergraduate textbook introduces students to the main ideas of statistics in a way that focuses on deep comprehension rather than rote application or mathematical immersion. The presentation of statistical concepts is thoroughly modern, sharing cutting-edge ideas from the fields of machine learning and data science that help students effectively use statistical methods to ask questions about data. Statistical Thinking provides the tools to describe complex patterns that emerge from data and to make accurate predictions and decisions based on data.

  • Introduces statistics from a uniquely modern standpoint, helping students to use the basic ideas of statistics to analyze real data
  • Presents a model of statistics that ties together a broad range of statistical techniques that can be used to answer many different kinds of questions
  • Explains how to use statistics to generate reproducible findings and avoid common mistakes in statistical practice
  • Includes a wealth of examples using real-world data
  • Accompanied by computer code in R and in Python—freely available online—that enables students to see how each example is generated and to code their own analyses

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Yes, you can access Statistical Thinking by Russell Poldrack in PDF and/or ePUB format, as well as other popular books in Psychology & Applied Psychology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Contents
  3. Preface
  4. 1. Introduction
  5. 2. Working with Data
  6. 3. Summarizing Data
  7. 4. Data Visualization
  8. 5. Fitting Models to Data
  9. 6. Probability
  10. 7. Sampling
  11. 8. Resampling and Simulation
  12. 9. Hypothesis Testing
  13. 10. Quantifying Effects and Designing Studies
  14. 11. Bayesian Statistics
  15. 12. Modeling Categorical Relationships
  16. 13. Modeling Continuous Relationships
  17. 14. The General Linear Model
  18. 15. Comparing Means
  19. 16. Multivariate Statistics
  20. 17. Practical Statistical Modeling
  21. 18. Doing Reproducible Research
  22. Bibliography
  23. Index