Tool Box (detail: "http://datasciencespecialization.github.io/toolbox/")

Week Two R & RStudio

1. Packages
   CRAN (Comprehensive R Archive Network): R’s main repository (>12,100 packages available!) https://cran.r-project.org/web/packages/
   BioConductor: A repository mainly for bioinformatic-focused packages https://bioconductor.org/packages/release/BiocViews.html#___Software

Week Three Linked Rstudio and Git

1. Create repo and change from Rstudio
   e.g. Testing.R (initial script)

Week Four

1. Using R markdown commands:
   1)section headers:
   "# Header level 1"
   "## Header level 2"
   "### Header level 3..."
   2)R code chunk: Ctrl+Alt+I (Windows) or Cmd + Option + I (Mac)
2. Types of data science questions:
   Descriptive analysis
   Exploratory analysis
   Inferential analysis(use a relatively small sample of data to infer or say something about the population at large)
   Predictive analysis
   Causal analysis
   Mechanistic analysis(exact changes in variables that lead to exact changes in other variables)

R Programming