Introduction to R and Statistical Computing

Vakbeschrijving Introduction to R and Statistical Computing
Collegejaar: 2018-2019
Studiegidsnummer: 6464MS11
Docent(en):
  • Dr. F.M.T.A. Busing
  • Drs. B.C. Pratiwi
Voertaal: Engels
Blackboard: Ja
EC: 5
Niveau: 500
Periode: Semester 1 / 2, Blok I, III
Onderwijstijd in uren
(excl. zelfstudie):
35:00 uur
  • Geen Keuzevak
  • Geen Contractonderwijs
  • Geen Exchange
  • Geen Study Abroad
  • Geen Avondonderwijs
  • Geen A-la-Carte en Aanschuifonderwijs
  • Geen Honours Class

Entry requirements

Only open to Master’s and Research Master’s students from Psychology.

Description

R is a popular statistical programming environment, which provides a wide variety of statistical analysis tools, like data manipulation, model construction, simulations, and visualization. It can be used as data analysis software, but also as an effective programming language. In addition, R is available as Free Software, underlying code can be viewed and the researcher can make changes to suit his needs. Due to this open nature, R is highly flexible and can easily be extended, either by adding packages or programming new functions. Therefore R contains an ever-growing large collection of tools for data analysis, making it the primary tool of many researchers and a cutting edge environment for statisticians.

This course will give an introduction to R and computational statistics, handing a toolkit of theory and practice of the environment, making it both possible to use R in a variety of statistical analysis, and creating a base for acquiring further knowledge and skill.

Course objectives

Upon completion of this course, the student:
* Knows how to use R and its environment and how to get help;
* Knows how to handle simple data and functions;
* Knows how to handle complex data and functions;
* Knows how to handle graphs;
* Knows how to handle different data analyses;
* Knows how to program in R;
* Knows how to do matrix algebra in R;
* Knows how to handle optimization, that is, finding the optimum of a function; and
* Knows how to perform random number generation, Monte Carlo simulation, and re-sampling.

Timetable

For the timetables of your lectures, work groups and exams, please select your study programme in:
Psychology timetables

Lectures

Registration

Course

Students need to enroll for lectures and work group sessions.
Master’s course registration

Examination

Students are not automatically enrolled for an examination. They can register via uSis from 100 to 10 calendar days before the date. Students who are not registered will not be permitted to take the examination.
Registering for exams

Mode of instruction

The course consists of:
* 8 2-hour lectures and
* 8 2-hour work group sessions.

Assessment method

Asssessment for this course consists of 2 assignments. The final grade is a weighted average of these 2 graded assignments.
The last assignment forms the basis of an oral examination.

The Institute of Psychology follows the policy of the Faculty of Social and Behavioural Sciences to systematically check student papers for plagiarism with the help of software. Disciplinary measures will be taken when fraud is detected. Students are expected to be familiar with and understand the implications of this fraud policy.

Reading list

Manuals and articles are available from Blackboard during the course.

Contact information

Dr. Frank Busing
busing@fsw.leidenuniv.nl
Drs. Bunga Pratiwi
Bunga.pratiwi@fsw.leidenuniv.nl

Talen