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Statistical Thinking for the 21st Century Russell Poldrack

Contributor(s): Material type: TextTextSeries: Open textbook libraryDistributor: Minneapolis, MN Open Textbook LibraryPublisher: Stanford, California Russell Poldrack [2018]Copyright date: ©2018Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
Subject(s): LOC classification:
  • BF121
  • QA37.3
  • QA273-280
Online resources:
Contents:
1 Introduction -- 2 Working with data -- 3 Probability -- 4 Summarizing data -- 5 Fitting models to data -- 6 Data Visualization -- 7 Sampling -- 8 Resampling and simulation -- 9 Hypothesis testing -- 10 Confidence intervals, effect sizes, and statistical power -- 11 Bayesian statistics -- 12 Modeling categorical relationships -- 13 Modeling continuous relationships -- 14 The General Linear Model -- 15 Comparing means -- 16 The process of statistical modeling: A practical example -- 17 Doing reproducible research
Subject: Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.
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1 Introduction -- 2 Working with data -- 3 Probability -- 4 Summarizing data -- 5 Fitting models to data -- 6 Data Visualization -- 7 Sampling -- 8 Resampling and simulation -- 9 Hypothesis testing -- 10 Confidence intervals, effect sizes, and statistical power -- 11 Bayesian statistics -- 12 Modeling categorical relationships -- 13 Modeling continuous relationships -- 14 The General Linear Model -- 15 Comparing means -- 16 The process of statistical modeling: A practical example -- 17 Doing reproducible research

Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.

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In English.

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