Group | Type | Day | Time | Classroom | Weeks | Comment |
---|---|---|---|---|---|---|
Common | I | Tuesday | 12-14 | U55 | 14-15, 17-21 | |
Common | I | Thursday | 08-10 | U55 | 20-21 | |
Common | I | Friday | 12-14 | U140 | 14 | |
Common | I | Friday | 12-14 | U55 | 15,17,19 | |
Common | I | Friday | 12-14 | U37 | 18 | |
M1 | TE | Monday | 14-16 | U49E | 15-16, 18-21 | |
M1 | TL | Wednesday | 14-16 | U10b | 15, 18 | |
M1 | TE | Wednesday | 14-16 | U17 | 17, 19, 21 | |
S1 | TE | Tuesday | 10-12 | U17 | 15, 17-21 | |
S1 | TL | Wednesday | 10-12 | U10b | 15, 18 | |
S1 | TE | Friday | 10-12 | U17 | 17, 19, 21 | |
S2 | TE | Monday | 10-12 | U49D | 15-16, 18-21 | |
S2 | TE | Tuesday | 10-12 | U49D | 17, 19, 21 | |
S2 | TL | Tuesday | 10-12 | U10b | 18 | |
S2 | TL | Friday | 14-16 | U10b | 15 | |
S3 | TE | Tuesday | 14-16 | U49D | 15, 17-21 | |
S3 | TL | Friday | 08-10 | U10b | 15, 18 | |
S3 | TE | Friday | 08-10 | U14 | 17, 19, 21 | |
S4 | TE | Tuesday | 14-16 | U17 | 15, 17-21 | |
S4 | TL | Wednesday | 08-10 | U10b | 15, 18 | |
S4 | TE | Thursday | 10-12 | U49D | 17, 19, 21 | |
S5 | TL | Monday | 12-14 | U10b | 15, 18 | |
S5 | TE | Monday | 12-14 | U49D | 16, 19, 21 | |
S5 | TE | Wednesday | 08-10 | U17 | 15, 17-21 |
Ubegrænset deltagerantal. 4. kvartal.
Prerequisites:
None
Academic preconditions:
The contents of the courses Calculus I and II must be known.
Course introduction
To introduce elementary methods from probability theory and statistics with a view to analysing experimental data. The participants will learn to use a statistical computer package for data analysis.
Expected learning outcome
At course end the student will be able to:
• identify problems that can be solved by means of statistics and probability;
• plan the collection of data and calculating sample sizes;
• describe data using graphical and numerical methods from descriptive data analysis;
• perform simple probability calculations using distributions and random variables;
• know standard probability models and identify their areas of application;
• model experimental data using simple statistical models;
• check the correctness of a statistical model;
• estimate parameters in a simple statistical model, and calculating confidence intervals for the parameters;
• test simple statistical hypotheses and interpret the results;
• analyze data using simple regression methods;
• apply a statistical computer package for carrying out simple statistical calculations;
• evaluate critically the relevance of the methods applied and the ensuing inferences;
• formulate statistical results in non-technical terms.
Subject overview
Descriptive data analysis, experimental design, probability, random variables, mean, variance, co-variance, standard probability models, parameter estimation, confidence intervals, hypothesis tests, regression, comparison of groups.
Literature