Data analysis with RMethodology courses and philosophy of science


Course information


ECTS: 1
Number of sessions: 4
Hours per sessions:
3
Entry level: Introduction
Course fee:

  • This workshop is exclusively for PhD candidates of the Graduate School. 
  • consult our enrolment policy for more information
  • You can only enrol for one edition of this course

    Contact:

    Telephone: +31 (0)10 4082607


    Edition I

    March 5 (Monday) 2018
    09.30-12.30
    Mandeville building (directions) room T18-04

    March 9 (Friday) 2018
    09.30-12.30
    Mandeville building (directions) room T18-04

    March 12 (Monday) 2018
    09.30-12.30
    Mandeville building (directions) room T18-04

    March 16 (Friday) 2018
    09.30-12.30
    Mandeville building (directions) room T18-04

    Edition II

    March 5 (Monday) 2018
    13.30-16.30
    Mandeville building (directions) room T18-41

    March 9 (Friday) 2018
    13.30-16.30
    Mandeville building (directions) room T18-03

    March 12 (Monday) 2018
    13.30-16.30
    Mandeville building (directions) room T18-04

    March 16 (Friday) 2018
    13.30-16.30
    Mandeville building (directions) room T3-01


    Introduction

    The open-source software environment R is a powerful platform for data analysis and statistical graphics that has become the global standard in statistical computing. It combines a powerful programming language with flexible graphical capabilities.


    Aims and working method

    The instructor will illustrate the application of these techniques with practical examples of R. Participants will gain practical experience with R by conducting analyses on provided datasets or data from the participants’ PhD project.


    Learning objectives

    • Understand basic R functionality for reading and manipulating data sets
    • Explore data with descriptive statistics and graphics
    • Use R for more advanced analyses (such as, linear regression modelling and mediation and moderation)

    How to prepare

    • Bring your laptop to all session
    • Download and install RStudio

    Installation instruction:

    • Log in to your remote desktop and open the application catalog
    • Search for 'RStudio'
    • Download and install R 3.4.1 / RStudio 1.0.143 
    • Search for 'application catalog' and/or 'remote desktop' in myeur.nl for more information.
    • Please do this well in advance and notify the course instructor if there are any problems

    Session description

    Session 1
    Understanding R

    Session 2
    Using R for data analysis


    About the instructor

    Pieter Schoonees is an assistant professor in the Department of Marketing Management at RSM, Erasmus University. His expertise lie in the fields of computational statistics, machine learning and psychometrics. Pieter's research focuses on developing statistical and machine learning algorithms and applying these to secondary data. A special interest is the use of such techniques for the analysis of data gathered from neuroscienfic studies.