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
Statistical Thinking: Analyzing Data In An Uncertain World
β Scribed by Russell A. Poldrack
- Publisher
- Princeton University Press
- Year
- 2023
- Tongue
- English
- Leaves
- 281
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β’ Introduces statistics from a uniquely modern standpoint, helping students to use the basic ideas of statistics to analyze real data
β’ 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
β’ Explains how to use statistics to generate reproducible findings and avoid common mistakes in statistical practice
β’ Includes a wealth of examples using real-world data
β’ Accompanied by computer code in R and in Pythonβfreely available onlineβthat enables students to see how each example is generated and to code their own analyses
β¦ Table of Contents
Cover
Half Title
Title
Copyright
Contents
Preface
1. Introduction
2. Working with Data
3. Summarizing Data
4. Data Visualization
5. Fitting Models to Data
6. Probability
7. Sampling
8. Resampling and Simulation
9. Hypothesis Testing
10. Quantifying Effects and Designing Studies
11. Bayesian Statistics
12. Modeling Categorical Relationships
13. Modeling Continuous Relationships
14. The General Linear Model
15. Comparing Means
16. Multivariate Statistics
17. Practical Statistical Modeling
18. Doing Reproducible Research
Bibliography
Index
β¦ Subjects
Statistics; Social Sciences: Statistical Methods
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Includes bibliographical references and index