Lecture 1: Intro to Course

• “Hi, I'm Nathan”
• Who are R you?
• Does everyone have R?
• Key themes of course
• Does everyone have RStudio?
• The Basics of R
• The Basics of RStudio
• Intro to RMarkdown

• Dr. for just over 365 day

• Statistical fundamentals: getting the basics right, b/c many biologists get them wrong! (random sampling, what is a p-value, what is a confidence interval, power)
• Modern methods in biostats: multiple regression, logistic regression, mixed effects models, multivariate stats, meta-analysis
• Contemporary issues in stats: ie. The “replication crisis” in some fields, p-hacking, hierarchical/multilev. models, big data, false discovery rate
• Doing statistics in R: We'll do all of the above hands-on, in R
• Doing graphis in R with ggplot: ggplot is probably the most powerful scientific tool known to humankind (well, close).
• Doing reproducible research in R: documenting what you do using RMarkdown and other tools

• Use R carry out analyses & make graphics using ggplot to include in your dissertation
• Understand why those analyses are appropriate
• Be better able to review the stats of other researchs (labmates, peer review, your PI…)
• Know where to look for help for advanced topics
• Use the basic principals and tools of reproducible research

summary(cars)

     speed           dist       
 Min.   : 4.0   Min.   :  2.00  
 1st Qu.:12.0   1st Qu.: 26.00  
 Median :15.0   Median : 36.00  
 Mean   :15.4   Mean   : 42.98  
 3rd Qu.:19.0   3rd Qu.: 56.00  
 Max.   :25.0   Max.   :120.00