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Mathematical Statistics 7,5 Credits

The course focus on the basic proability theory and relevant statistical inference methods that are used when analyzing a data set. Random variability is a fundamental concept.

Course Contents

The course focuses on basic proability theory and relevant statistical inference methods that are used when analyzing a data set. Random variability is a fundamental concept.

The course includes the following elements:
- Basic probability theory
- Random Variables
- Discrete and continuous distributions, especially the normal distribution
- The Central limit theorem with applications
- Descriptive statistics
- Point estimates and interval estimates
- Hypothesis testing
- Simple linear regression analysis
- Correlation

Prerequisites

General entry requirements and completed course Single Variable Calculus, 7,5 credits (or the equivalent).

Level of Education: Undergraduate G1F
Course code/Ladok code: TMSK17
The course is conducted at: School of Engineering