Name: Statistical Thinking: Analyzing Data in an Uncertain World (en Inglés)
SKU: 55592428
Price: 106.74 USD
Availability: InStock
Author: Russell Poldrack

portada Statistical Thinking: Analyzing Data in an Uncertain World (en Inglés)

Statistical Thinking: Analyzing Data in an Uncertain World (en Inglés)

Formato

Libro Físico

Editorial

Princeton University Press

Autor

Russell Poldrack

Idioma

Inglés

N° páginas

280

Encuadernación

Tapa Dura

ISBN13

9780691250939

Statistical Thinking: Analyzing Data in an Uncertain World (en Inglés)

Russell Poldrack (Autor) · Princeton University Press · Tapa Dura

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Reseña del libro "Statistical Thinking: Analyzing Data in an Uncertain World (en Inglés)"

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 dataPresents a model of statistics that ties together a broad range of statistical techniques that can be used to answer many different kinds of questionsExplains how to use statistics to generate reproducible findings and avoid common mistakes in statistical practiceIncludes a wealth of examples using real-world dataAccompanied 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