Group | Type | Day | Time | Classroom | Weeks | Comment |
---|---|---|---|---|---|---|
Common | I | Monday | 14-16 | u1 | 36,43 | |
Common | I | Monday | 14-16 | u2 | 37 | |
Common | I | Monday | 14-16 | u47 | 39 | |
Common | I | Tuesday | 10-12 | u20 | 36-41,43 | |
S1 | TL | Monday | 14-17 | u10b | 41 | |
S1 | TL | Friday | 12-15 | u10b | 36,38,41 | |
S1 | TE | Friday | 08-10 | u26 | 37-41,43 | |
S2 | TL | Tuesday | 14-17 | u10b | 36,38,40-41 | |
S2 | TE | Thursday | 08-10 | u26a | 37-41,43 |
Evaluering d.31.10.2005
05.10.2005:Skemaændring
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.
Acquired skills:
The participants will acquire understanding of elementary probability theory and statistical methods, and their applications in experimental data. They will know how to apply this knowledge in relevant situations for:
• using graphical methods for descriptive data analysis;
• describing data using summary statistics, such as mean, variance and co-variance;
• modelling experimental data using statistical models;
• estimating parameters in statistical models, and constructing confidence intervals for the parameters;
• testing simple statistical hypotheses;
• analysing data using regressions- and calibration models;
• designing experiments;
• interpreting statistical data analyses and expressing the results in writing.
Expected learning outcome
Subject overview
Descriptive data analysis, probability models, random variables, mean, variance, co-variance, statistical models, parameter estimation, confidence intervals, regression, calibration, t-test, z-test, experimental design.
Literature