CRG PhD Course 2017 Introduction to Statistics in R

From Bioinformatics Core Wiki

Course Description

This introductory course to exploratory data analysis and R is offered in 3 two-hour consecutive modules (please see Course Syllabus below), each consisting of a hands-on practicum in a computer class, using R Studio.

Course Objectives

To introduce or to refresh the basic concepts of descriptive statistics and how they can be applied to real-life datasets using R. The students will produce their first scripts that can be re-used when they start analyzing their own data. Knowledge of statistics or R is not required for taking this course. However, familiarity with the material in the previous modules is recommended if the modules are not taken in a sequence.

Course Instructors

  • Sarah Bonnin (Module I, II)
  • Julia Ponomarenko (organizer, Module II, III)

Time and Location

  • Oct 3, 4, 5, 2017. 11:00 - 13:00. PRBB Building. Boinformatics classroom. 468. 4th floor. The hotel wing.

Course Syllabus, Schedule, and Materials

MODULE I. Introduction to R. Oct 3, 2017.

  • Introduction to R:
    • What is R?
    • Why to use R?
  • R studio:
    • Local installation
    • Understand and explore panels
  • Basics of R language:
    • Simple arithmetic in R console
    • Syntax
    • Objects
  • Functions in R:
    • Use functions
    • Get help
    • Arguments in functions
  • Data types and data structures in R
    • Types: numeric, character, logical.
    • Structures: vectors, data frames, matrices.
  • Slides for Module I: Open the pdf file.

MODULE II. Descriptive Statistics & Plots in R. Oct 4, 2017.

MODULE III. Introduction to Statistical Inference. Oct 5, 2017.

External Resources

Bioinformatics Core Facility @ CRG — 2011-2019