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Statistics 355
Biostatistics
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Textbook
Fundamentals of Biostatistics, 7th Edition,
by Bernard Rosner - Harvard University and Harvard Medical School,
Cengage Learning, 2011, ISBN-10: 0538733497, ISBN-13: 9780538733496
R Programming for Biostatistics
These notes illustrate the use of the R programming language and programming environment in support of a course on biostatistics. The scripts follow discussions in the text
Fundamentals of Biostatistics,
by Bernard Rosner, complement its study guide, and make use of its data sets. They do not include solutions to any of the exercises in that book.
- 1. General Overview
- 2. Descriptive Statistics (R script)
- 3. Probability (R script)
- 4. Discrete Probability Distributions (R script)
- 5. Continuous Probability Distributions (R script)
- 6. Estimation (R script)
- 7. Hypothesis Testing: One-Sample Inference (R script)
- 8. Hypothesis Testing: Two-Sample Inference (R script)
- 9. Nonparametric Methods (R script)
- 10. Hypothesis Testing: Categorical Data (R script)
- 11. Regression and Correlation Methods (R script)
- 12. Multisample Inference (R script)
- 13. Design and Analysis Techniques for Epidemiologic Studies
- 14. Hypothesis Testing: Person-Time Data
Schedule for Spring 2012
R Programming Notes
- packages : beanplot, ggplot2, knitr, RColorBrewer, xtable
- notes1 : str, bar chart, quantiles
- notes2 : stem-and-leaf diagram, frequency distribution, box plot
- notes3 : numerical measures, descriptive statistics
- notes4 : Wilcoxon signed rank test
- notes5 : Chi-square, Fisher's exact, and McNemar's tests
- notes6 :
standardized and studentized residuals
t test for simple linear regression
sample (Pearson) correlation coefficient, r
Fisher's Z transformation of r
- notes7 : ggplot : scatterplots, density plots, density plots with superimposed pdf, boxplots
- notes8 : scatterplot3d
- notes9 : options for plot
- notes10 : polygon code for shading plots
- notes11 : scatterplots
- notes12 : R notes and tutorials
- notes13 : illustrating rejection regions and the power of a statistical test
- notes14 : package `RColorBrewer'
- notes15 : annotated images : adding text and arrows
- notes16 : beanplot
- notes17 : manipulate : sliders in RStudio
- notes18 : contour plot
- notes19 : tikz
- notes20 : cluster analysis
- notes21: Efron-Tibshirani bootstrap
- notes22 : assumptions of the linear model (regression)
- notes23 : surface plots with persp and wireframe
- notes23 : transparent surface plots with wireframe
References
Professor
Chris Parrish
Office: Woods Laboratories 120
email: cparrish@sewanee.edu
cparrish@sewanee.edu