PSL4040H - Big Data and Health

Course Coordinator:  B. Cox

This is an interactive, hands-on workshop-style graduate course to learn how to apply the programming language R to analysis of data.  This course will focus on graphing, statistical modelling and prediction methods of data sets with clinical (patient treatments and diagnosis), biological (gene expression) and physiological (telemetry time series information) importance.  Students do not need to have prior computer science or programing experience.  A degree in physiology or biological sciences is recommended and an introductory statistic course is beneficial.  Basic principals in statistics will be reviewed in conjunction with their application in programming and data analysis.

Learning Objectives & Content:

By the end of the course students will have learned to:

1) Program in R, including:
  -  R syntax and core programming principals
  - data input and output
  - creating and defining data objects
  - plotting and graphing
2) Data analysis, including:
  - application of statistical tests in R
  - interpretation of statistical tests of data sets
3) Apply appropriate graphical and statistical analysis to different data types
  -best practices and methods to generate prediction models of data sets
4) Create R markdown reports of data analyses for communication of results

Classes will take place twice per week as 2-hour sessions