 Email: p.v.larsen@stat.sdu.dk
 Email: p.v.larsen@stat.sdu.dk| 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