Learning Statistics with R A tutorial for psychology students and other beginners Danielle Navarro
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TextSeries: Open textbook libraryDistributor: Open Textbook Library Publisher: Danielle Navarro Description: 1 online resourceSubject(s): Mathematics -- Textbooks | Social sciences -- Textbooks | Applied mathematics -- Textbooks | Psychology -- TextbooksLOC classification: QA1H1QA37.3QA37.3BF121Online resources: Access online version | Item type | Current library | Call number | URL | Status | Date due | Barcode | Item holds |
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eBook
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Online Access | QA1 (Browse shelf(Opens below)) | Link to resource | Available |
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
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.
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In English.
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