Intermediate Statistics with R Mark Greenwood
Material type:
- text
- computer
- online resource
- QA1
- QA37.3
- QA273-280
1 Preface -- 2 (R)e-Introduction to statistics -- 3 One-Way ANOVA -- 4 Two-Way ANOVA -- 5 Chi-square tests -- 6 Correlation and Simple Linear Regression -- 7 Simple linear regression inference -- 8 Multiple linear regression -- 9 Case studies
Introductory statistics courses prepare students to think statistically but cover relatively few statistical methods. Building on the basic statistical thinking emphasized in an introductory course, a second course in statistics at the undergraduate level can explore a large number of statistical methods. This text covers more advanced graphical summaries, One-Way ANOVA with pair-wise comparisons, Two-Way ANOVA, Chi-square testing, and simple and multiple linear regression models. Models with interactions are discussed in the Two-Way ANOVA and multiple linear regression setting with categorical explanatory variables. Randomization-based inferences are used to introduce new parametric distributions and to enhance understanding of what evidence against the null hypothesis “looks like”. Throughout, the use of the statistical software R via Rstudio is emphasized with all useful code and data sets provided within the text. This is Version 3.0 of the book.
Attribution-NonCommercial
In English.
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