4.9 KiB
| title | description |
|---|---|
| Probability and Statistics | Historical course details for Probability and Statistics, recovered from the previous Incognito wiki. |
:::caution[Historical information] This information originated in the previous wiki and may be outdated. Check the current Maastricht University course information before relying on it. :::
Full course description
Probability and Statistics introduces the student to the main concepts of probability theory and statistics. Probability theory is the mathematical branch that focuses on experiments where the outcome is determined by chance. Here students learn how to make use of random variables to extract the probability distribution of an experiment. Additionally topics such as, expectation, standard deviation, and independence will be examined. The statistics part of the course discusses basic statistical topics such as the central limit theorem, verification of hypotheses, and confidence intervals. After completing this course students will have obtained an overview of commonly seen probability distributions, as well as several statistical procedures. Additionally the student will be able to deal with problems that involve probabilities, and measure their outcome.
Prerequisites
None.
Recommended reading
None.
Files
- Exam 2016
- Exam 2016 - Solutions
- Exam Concept Sheet 2016
- Lecture -Random Variables
- Lecture 5 - Expectation Variance
- Lecture 6 Random Variables
- Lecture 7 - Discrete Distributions
- Lecture 8 - Continuous Distributions
- Lecture 9 - Gaussian Distribution
- Lectures 1 And 2
- Lectures 3 And 4
- Lectures 3 And 4 Handwritten Notes
- Notes - Expectation Variance Tail Inequalities
- P S Assignment 1
- P S Assignment 1 - Solutions
- P S Assignment 2
- P S Assignment 2 - Solutions Updated
- P S Assignment 3
- P S Assignment 3 - Solutions
- Ps Cheatsheet
- Ps Exam 2010-10-28
- Ps Exam 2012-10-23
- Ps Exam Solutions 2010-10-28
- Scanned Lecture Notes - Lectures 3-5
- Summary P S 2020 First6lectures
Source: Previous wiki page