Learning outcomes

Statistical ideas may be expressed most precisely and economically in mathematical terms. Contact with data and scientific inference give statistics a distictive outlook. A uniting idea is that of a statistical model.

Contents

Random variable, numerical charasteristics of a random variable, some special distributions, joint distribution of random variables, independence of random variables, moment-generating function, covariance and correlation of two random variables, transformation of random variables, the weak law of large numbers.

Teaching methods

Teaching method	Contact	Online
Lectures	26 h	0 h
Exercises	12 h	0 h

Teaching language

Finnish

Evaluation

Numeric 1-5.

Recommended year of study

2. year autumn

Study materials

1. Lecture notes in Finnish
2. Casella, G., Berger, R. L., Statistical inference. Duxbury Press 2002.
3. Hogg, R. V., Tanis, E. A., Probability and statistical inference. Prentice Hall 2001.
4. Huuhtanen, P., Kallinen, A., Matemaattinen tilastotiede. Tampereen yliopisto 1998.
5. Laininen, P., Todennäköisyys ja sen tilastollinen soveltaminen. Otatieto 2001.
6. Liski, E., Matemaattinen tilastotiede. Tampereen yliopisto 2005.
7. Tuominen, P., Todennäköisyyslaskenta I. Limes 1996.
8. Ross, S., A first course in probability. Prentice Hall 2005.

Belongs to following study modules