Learning Statistics with R A tutorial for psychology students and other beginners

Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writi...

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Bibliographic Details
Main Author: Navarro, Danielle (Author)
Format: Electronic eBook
Language:English
Published: Kensington, Australia Danielle Navarro [2018]
Series:Open textbook library.
Subjects:
Online Access:Access online version
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505 0 |a I. Background -- Chapter 1: Why do we learn statistics? -- Chatper 2: A brief introduction to research design -- II. An introduction to R -- Chapter 3: Getting started with R -- Chapter 4: Additional R concepts -- III. Working with data -- Chapter 5: Descriptive statistics -- Chapter 6: Drawing graphs -- Chapter 7: Pragmatic matters -- Chapter 8: Basic programming -- IV. Statistical theory -- Prelude -- Chapter 9: Introduction to probability -- Chapter 10: Estimating unknown quantities from a sample -- Chapter 11: Hypothesis testing -- V. Statistical tools -- Chapter 12: Categorical data analysis -- Chapter 13: Comparing two means -- Chapter 14: Comparing several means (one-way ANOVA) -- Chapter 15: Linear regression -- Chapter 16: Factorial ANOVA -- VI. Other topics -- Chapter 17: Bayesian statistics -- Chapter 18: Epilogue -- References 
520 0 |a Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to 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. 
542 1 |f Attribution-ShareAlike 
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588 0 |a Description based on print resource 
650 0 |a Mathematics  |v Textbooks 
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650 0 |a Applied mathematics  |v Textbooks 
650 0 |a Psychology  |v Textbooks 
650 0 |a Statistics  |v Textbooks 
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856 4 0 |u https://open.umn.edu/opentextbooks/textbooks/559  |z Access online version