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  • Statistical Thinking: Analyzing Data in an Uncertain World by Russell Poldrack book cover
  • Statistical Thinking: Analyzing Data in an Uncertain World by Russell Poldrack book cover
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Statistical Thinking: Analyzing Data in an Uncertain World

by Russell Poldrack

Statistics as a way of reasoning about data

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AlbakiReads Editorial

Statistics as a way of reasoning about data

Russell Poldrack’s undergraduate textbook frames statistics as a toolkit for asking questions of data, describing complex patterns, and making predictions and decisions amid uncertainty. Its organizing approach connects a broad range of statistical techniques, with emphasis on understanding their ideas rather than relying on rote procedures or extensive mathematical treatment. Examples draw on real-world data, while companion code in R and Python lets students follow how analyses are produced and try coding their own. The book also addresses reproducibility and common errors in statistical practice, placing statistical methods in the context of psychology and the social sciences.

Good fit for readers who enjoy

  • Undergraduate students in psychology or the social sciences beginning statistics
  • Learners who want conceptual understanding alongside practical data analysis
  • Students interested in working through examples with R or Python

Themes

Statistical reasoning and uncertaintyData analysis and predictionReproducible researchStatistical practice in psychology and social sciences

Based on publisher information and book metadata.

Book overview

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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