|Teaching method||Contact hours|
|Practical intensively supervised||12|
Language of instruction:
Practical notion of probability; basic probability theory; derivation of the binomial distribution; normal distribution; principles of hypothesis testing for the binomial test; normal approximation (z-test); properties of the mean of a normal random sample as an estimator of a population mean; basic notion of consistency.
After this course, the student is expected to be able to:
- demonstrate a practical notion of probability;
- perform simple probability calculus;
- calculate probabilities for the binomical and normal distributions;
- reproduce the principles of hypothesis testing;
- perform a binomial test;
- demonstrate understanding of the consistency of an estimator.
Tutorials, including making exercises, and (compulsory) computer practicals, analyzing data. Attend presentations that are motivated by practical problems from the Life Sciences. Prepare and hand in a brief report on a case study.
Multiple-choice exam. The practical has to result in a pass.
Statistical Methods and Data Analysis by R. Lyman Ott and Michael Longnecker (ISBN 0495109142; 6th edition). A Study Guide provides an introduction to tutorials and practicals, and recommended exercises and background reading from the book (WUR Shop)