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Data & Analytics 3: Mathematics & Statistics
level of course unit
BachelorLearning outcomes of course unit
- Students can carry out mathematical modeling for practical problems in computer science and economics and find solutions using methods of differential and integral calculus.
- Students can correctly record, describe, analyze, and interpret statistical data and apply basic methods of inferential statistics, in particular, elementary estimation methods and simple test methods.
- Students can correctly record, describe, analyze, and interpret statistical data and apply basic methods of inferential statistics, in particular, elementary estimation methods and simple test methods.
prerequisites and co-requisites
none
course contents
- Repetition of the concept of function and some important functions
- Differential calculus and its application in one and several variables
- Elementary introduction to integral calculus
- Descriptive statistics: basics, location and scattering ratios, regression and correlation
- Probability theory: terminology, basic properties, rules, and the concept of discrete and continuous random variables
- Inductive statistics: basics, simple estimation methods, simple test methods
- Differential calculus and its application in one and several variables
- Elementary introduction to integral calculus
- Descriptive statistics: basics, location and scattering ratios, regression and correlation
- Probability theory: terminology, basic properties, rules, and the concept of discrete and continuous random variables
- Inductive statistics: basics, simple estimation methods, simple test methods
recommended or required reading
Coming soon
assessment methods and criteria
Portfolio review
language of instruction
Germannumber of ECTS credits allocated
6eLearning quota in percent
20course-hours-per-week (chw)
3planned learning activities and teaching methods
Lectures, tutorials (in connection with lecture/seminar), group work
