Version: 03 November 2020

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Todays goals

  • Introduction to the idea of Data Science
  • Getting an overview of the content of this seminar
  • Installing R on your computer
  • Installing R-Studio on your computer
  • Overview of R-Studio

What is R?

  • A tool for statistical computation (like SPSS, Mplus, STATA …)
  • A programming language
  • An idea and a community that shares common ideas about science

Statements

  • Science should be truthfull
  • Science should be diligent
  • Science should be transparent
  • Science should be reproducible
  • Science should be communicated
  • Science should be accessible
  • Science should be open

R (and R studio) help with …

  • Science should be truthfull
  • Science should be diligent
  • Science should be transparent
  • Science should be reproducible
  • Science should be communicated
  • Science should be accessible
  • Science should be open

What R can do

Any kind of statistical analyses:

  • Descriptive stats
  • Modelling
  • Inferential stats
  • Manage and organize data
  • Large data (large scale / big data / EEG / fMRT)
  • Small data (experimental data / questionnaire data / single-case data)

Present data

  • Visualize data and results
  • Keep a notebook of your research and analyses
  • Write reports, including stats
  • Write presentations
  • Write books
  • Build interactive websites
  • Connect with various other software and internet tools

Schedule

# Topic
1 Installation R and R Studio
2 Basics of R, part 1
3 Basics of R, part 2
4 Markdown part 1
5 Markdown part 2
6 Data manipulation with tidyverse part 1
7 Data manipulation with tidyverse part 2

# Topic
8 Basic statistics
9 Data visualizazion with ggplot2, part 1
10 Data visualizazion with ggplot2, part 2
11 Regression analyses with R
12 Multilevel Regressions

Installation of R and R-Studio

Installing R

Installing R-Studio

R for Data science