Learning Statistics with R

Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on using the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R and introduces data manipulation and writing scripts.

From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.

Learning Statistics with R
Learning Statistics with R

Author

Danielle Navarro, PhD is a computational cognitive scientist at the University of New South Wales. Her research focuses on human concept learning, reasoning and decision-making. She is also interested in language and cultural evolution, cognitive development, and statistical methods in the behavioural sciences

Contents

A brief introduction to research design11
Getting started with37
857
Additional R concepts73
Working with data111
Drawing graphs157
Pragmatic matters195
Basic programming253
22368
25375
Comparing two means381
33392
35403
Comparing several means oneway ANOVA427
Linear regression459
Factorial ANOVA499
Introduction to Probability275
Estimating unknown quantities from a sample301
1327
14348
Categorical data analysis351
18360
66532
Bayesian statistics557
Epilogue589
69599
Copyright

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