Statistical thinking
analyzing data in an uncertain world
- ISBN: 9780691218441
- Editorial: Princeton University Press
- Fecha de la edición: 2024
- Lugar de la edición: Princeton (NJ). Estados Unidos de Norteamérica
- Encuadernación: Rústica
- Medidas: 25 cm
- Nº Pág.: 280
- Idiomas: 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 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
Introduction
Working with data
Summarizing data
Data visualization
Fitting models to data
Probability
Sampling
Resampling and simulation
Hypothesis testing
Quantifying effects and designing studies
Bayesian statistics
Modeling categorical relationships
Modeling continuous relationships
The general linear model
Comparing means
Multivariate statistics
Practical statistical modeling
Doing reproducible research