URL study guide
https://tue.osiris-student.nl/onderwijscatalogus/extern/cursus?cursuscode=JBM015&collegejaar=2025&taal=enDescription
The following topics will be covered in the course:- Probability theory (the classical definition of probability, probability rules, conditional probability)
- Random variables, probability distributions, probability density functions
- (Conditional) Expectation, variance, standard deviation, covariance, correlation;
- Sampling theory
- Point estimators, confidence intervals, hypothesis testing
Estimation of the mean/variance using a random sample, confidence intervals and hypothesis testing for the (difference in) mean(s)
Objectives
After successfully completing the two parts of the course students will be able to:Part I
Perform elementary probability calculations with stochastic models
Identify situations where probabilistic models are adequate
Make use of probability distributions for modeling and analysis of situations where randomness occurs (or when it is considered to be a good modeling tool)
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Part II
Perform elementary statistical analyses of data
Use and construct point estimators, confidence intervals, and hypothesis tests
In addition to the above learning outcomes, students are expected to adequately document calculations that form the base of their probabilistic or statistical analysis.
Grading scheme:
The final grade will be based on two items:
3 homework assignments, the best 2 of which each count for 15% of the final grade.
A written exam (closed book) which counts for the remaining 70% of the final grade.
If you reach less than 50% of the points on the final exam equivalent to a 5.5 (given the grading scheme), then you will fail the course, regardless of the points you collected with the homework assignments. Your grade will be the minimum of 5 and the grade you achieved. However, you are allowed to participate in the second chance exam. The grade of the second chance exam replaces the grade for the first exam, that is, your homework assignments always count for 30% of your grade.
Contents
The following topics will be covered in the course:
Probability theory (the classical definition of probability, probability rules, conditional probability)
Random variables, probability distributions, probability density functions
(Conditional) Expectation, variance, standard deviation, covariance, correlation;
Sampling theory
Point estimators, confidence intervals, hypothesis testing
Estimation of the mean/variance using a random sample, confidence intervals and hypothesis testing for the (difference in) mean(s)