Chapter 1 Welcome

1.1 Course Objectives

This programming course in biohealth data science emphasizes statistics and hands-on learning. You will gain proficiency in R and RStudio, developing the skills to work independently in programming and data science workflows. The lectures cover two perspectives: developers and data analysts.

For developers, the first module focuses on:

  1. Learning the fundamentals of R programming using base R.
  2. Creating R packages, including code organization, testing, documentation, and sharing.
  3. Statistical Simulations

For data analysts, the second module covers:

  1. Importing, tidying, transforming, visualizing, and modeling data using existing tools.
  2. Best practices for workflows and reproducibility in data science.
  3. Applying statistical inference.

1.2 Target Students

These lectures target students who want to be:

  • Analysts employed by a hospital or government agency who produce statistical reports on a regular basis and need to develop production programs for this purpose
  • Academic researchers developing statistical methodology that is either new or combines existing methods into integrated procedures who need to codify this methodology so that it can be used by the general research community
  • Anyone developing code to produce sophisticated graphical presentations of data
  • Professional programmers with experience in software development
  • Statisticians/Data scientists evaluating performance of algorithms based on simulations

1.3 Resources

We will use various books and materials.

  1. The Art of R Programming (Matloff 2011)
  2. Hands-On Programming with R (Grolemund 2014)
  3. R for Data Science (Wickham, Çetinkaya-Rundel, and Grolemund 2023)
  4. R Packages (Wickham and Bryan 2023)

Materials are uploaded on a weekly basis.

References

Grolemund, Garrett. 2014. Hands-on Programming with r: Write Your Own Functions and Simulations. " O’Reilly Media, Inc.".
Matloff, Norman. 2011. The Art of r Programming: A Tour of Statistical Software Design. No Starch Press.
Wickham, Hadley, and Jennifer Bryan. 2023. R Packages. " O’Reilly Media, Inc.".
Wickham, Hadley, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023. R for Data Science. " O’Reilly Media, Inc.".