A Second Semester Statistics Course with R
Greenwood, Mark C.
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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 is emphasized with all useful code and data sets provided within the text. This is Version 4.0 of the text, updated in Fall 2017. The final chapter connects many of the methods covered in the general framework of linear models before applying the methods to three case studies extracted from recently published papers.
For use in STAT 217