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Course module: 424246-B-6
424246-B-6
Introduction to Statistical Science
Course info
Course module424246-B-6
Credits (ECTS)6
CategoryBA (Bachelor)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Social and Behavioral Sciences; TSB: Methodology and Statistics; Methodology and Statistics;
Is part of
B Psychology (Dutch)
B Psychology (English)
Minor Applied Advanced Research Methods
Minor Psychological Methods and Data Analysis
Lecturer(s)
Lecturer
prof. dr. M.A.L.M. van Assen
Other course modules lecturer
Lecturer
dr. J. Tijmstra
Other course modules lecturer
Academic year2019
Starting block
BLOK 2
Course mode
Full-time
Remarks-
Registration openfrom 07/10/2019 up to and including 21/08/2020
Aims

After taking this course, students can:

(Part I)

1. calculate probabilities and conditional probabilities of events, also using computer program PQRS

2. evaluate if statistical dependence holds or is violated

3. evaluate characteristics of probability density functions and apply them to different research problems

4. generate and evaluate a likelihood function for different research problems

(Part II)

5. note the difference between simulation studies, mathematical proofs, and empirical studies, and can evaluate if they can be used in particular research questions

6. identify problems that can be solved using simulation studies

7. conduct small-scale simulation studies and analyze their results using the R statistical software

8. interpret and apply data-analysis techniques based on simulations, such as the parametric bootstrap, nonparametric bootstrap and the permutation test

(Part III)

9. apply Bayes’ theorem to different research problems

10. evaluate and select appropriate prior distributions in Bayesian analysis

11. combine the prior distribution and likelihood function into the posterior distribution, using Bayes’ theorem

12. test statistical hypotheses using Bayes factors using the R software

Specifics

Each module contains 4 lectures and practicals. Assignments in the practicals consist of paper-and-pencil and computer questions, and are graded. The grades for each module are a weighted average of the grades for these assignments. The final grade for the course is the average grade of the three module grades. The student passes the course if the average grade of the three assignments is at least 5.5, with the proviso that none of the three assignments is lower than 4.5.

If students fail for the first exam of an academic year, they can retake of one to three of the individual modules. The retake of one module comprises one all-encompassing assignment. Grades of individual modules expire in the next academic year.

The grading of the course consists of two parts: the course exam (graded 1-10) and the SPSS practical (graded pass-fail). A student passes the course and receives the corresponding ects when he/she is graded a 6 or higher in the course exam and a pass in the SPSS practical. Both partial results remain valid after the academic year in which they were obtained.
 

Required Prerequisites

MTO-B on inferential statistics, MTO-C-MAW on causal analysis techniques, or at least one of MTO-C-PSY on Experimental Research Methods and MTO-D-PSY on Correlational Research Methods 1, or equivalent courses (subject to the decision of the programme director of MTO).

Recommended Prerequisites

Content

The course consists of three modules. The modules focus on basic and vital approaches in statistics to deal with research problems. The modules are (see objectives for more details):

1. Applied probability theory

2. Computer simulation 

3. Bayesian analysis

Type of instructions

Lectures and practicals

Type of exams

Individual assignments and resulting reports, one per module of the course

Compulsory Reading
  1. Will be announced via Blackboard at the beginning of the course..
Course available for exchange students
Conditions of admission apply
Contact person
prof. dr. M.A.L.M. van Assen
Timetable information
Introduction to Statistical Science
Written test opportunities
DescriptionTestBlockOpportunityDate
Written test opportunities (HIST)
DescriptionTestBlockOpportunityDate
Schriftelijk (Kansrekenen) / Written (Probability)EXAM_01BLOK 2120-12-2019
Schriftelijk (Kansrekenen) / Written (Probability)EXAM_01BLOK 2216-01-2020
Required materials
-
Recommended materials
To be announced
Will be announced via Blackboard at the beginning of the course.
Tests
Written (Probability)

Written (Bayes)

Final Result

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