Probability Theory and Descriptive Statistics (B-KUL-HBE08E)
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Aims
The overall objective of this course is for students to get acquainted with the basic principles of probability theory and descriptive statistics so that they can use the methods and techniques from these disciplines successfully to support policy decisions in the public and private sectors. The course "Probability Theory and Descriptive Statistics" contributes to the following competences:
- Acquiring a basic understanding of relevant scientific methods and techniques;
- Developing problem-solving;
- Analyzing, synthesizing and integrating various insights;
- Applying and assessing methods critically.
More specifically, upon completion of this course
- students can justify and explain the discussed statistical techniques, methods and probability rules, and apply them to concrete research;
- students have an understanding of statistical techniques and methods and probability rules;
- students can choose between the different available techniques and methods in specific situations;
- students are able to build a sound argument (from analyzing the problem to the solution and conclusion).
Previous knowledge
If you want to follow this course, it is advisable to have completed the following courses first:
- Mathematics for Business Engineers I (HBE01E)
- Mathematics for Business Engineers II (HBE02E)
Identical courses
This course is identical to the following courses:
D0H46A : Kansrekenen en beschrijvende statistiek
HBN65B : Kansrekenen en beschrijvende statistiek (No longer offered this academic year)
Is included in these courses of study
Activities
3 ects. Probability Theory and Descriptive Statistics (B-KUL-HBE08e)
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Content
The term probability, different definitions of probability, calculation rules, counting techniques, conditional probability, independent events, Bayes' rule.
Univariate random variables: specific discrete and continuous random variables, expected value, variance, moments and other key figures.
Discrete and continuous probability models, transformations of random variables
Multivariate random variables: joint, marginal, conditional probability distribution, specific probability distributions and densities. Functions of several random variables, covariance and correlation.
Law of large numbers, central limit theorem.
Descriptive statistics: data and their presentation (graphically and in tables), descriptive indicators of sample data, introduction to the software R.
Course material
The study materials will be made available through Toledo.
Format: more information
Lectures (2 hours per week).
About 6 practical sessions (2 hours each) spread over the semester. Students solve exercises on their own, including examples in the software R.
Evaluation
Evaluation: Probability Theory and Descriptive Statistics (B-KUL-H75212)
Explanation
In the exam period there is a written closed book examination that takes at most 3 hours. The lecturer will provide a formulary. The exam consists of exercises and (theoretical) questions related to knowledge and insight. Students may use a (graphing) hand calculator and the provided formulary. The exam counts for 80% of the final grade.
At the latest two weeks before the exam, students will be given an assignment. They are asked to analyze a data set with the statistical software package R and generate an output with relevant descriptive statistics (without writing down any comments). Before /during the aforementioned written examination, students will be interrogated orally (individually) about the generated output. During this oral examination also other questions related to the course can be asked. Students who just generate output without an oral clarification do not get the grades for this part. The same goes for students who do not bring the R output with them. The oral part counts for the remaining 20% of the grade.
Information about retaking exams
The features of the evaluation and determination of grades are identical to those of the first examination opportunity, as described in the tab 'Explanation'.