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Probability Theory and Statistics II - JEB012

Title:	Pravděpodobnost a matematická statistika II
Guaranteed by:	Institute of Economic Studies (23-IES)
Faculty:	Faculty of Social Sciences
Actual:	from 2010
Semester:	summer
E-Credits:	5
Examination process:	summer s.:
Hours per week, examination:	summer s.:2/2, Ex [HT]
Capacity:	unknown / unknown (unknown)
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	not taught
Language:	Czech
Teaching methods:	full-time
Additional information:	http://samba.fsv.cuni.cz/~visek/statistika/ (handouts in english - beamer-handouts version of lectures)
Note:	course can be enrolled in outside the study plan enabled for web enrollment priority enrollment if the course is part of the study plan

Guarantor:	prof. RNDr. Jan Ámos Víšek, CSc. Ing. Monika Hollmannová
Pre-requisite :	JEB011

Schedule Noticeboard

Annotation -

This course follows the course Probability Theory and Mathematical Statistics I (that course is required for selecting this one). Participants obtain an information about basic statistical methods and notions: random sample, various types of estimators and their properties, testing the hypotheses, Student§s tests, Fisher-Cochran theorem, very first look at robust staistics.

Last update: VISEK (14.04.2008)

Aim of the course -

To aply the theory of probability, studied in the winter term, to become familiar with basic notions of estimation of parameters and testing statistical hypotheses which are crucial for study of econometrics.

Last update: VISEK (14.04.2008)

Literature -

Breiman, L. (1968): Probability, Addison-Wesley Publishing Company, London 1968.

Lehmann, E. L. (1998): Theory of Point Estimation (Springer Texts in Statistics)

Lehmann, E. L. (1998): Testing Statistical Hypotheses, (Springer Texts in Statistics).

Rao, R. C. (1973): Linear Statistical Inference and Its Applications. New York: J.Wiley and Sons.

Vajda, I. (1989): Theory of Statistical Inference and Information. Dordrecht: Kluwer Academic Publication.

Last update: VISEK (14.04.2008)

Teaching methods -

Lectures with seminars.

Last update: VISEK (14.04.2008)

Requirements to the exam -

Writing reports - homeworks from seminars and passing tests for credits.

Last update: VISEK (14.04.2008)

Syllabus -

Point estimation and properties of estimators (unbiasedness, (root n)-consistency, asymptotic normality, efficiency, Rao-Cramer theorem, Student?s tests, Fisher-Cochran theorem), robust statistics.

Last update: VISEK (14.04.2008)

Entry requirements -

Passing mathematics (JEB005 a 006) and statistics (JEB011).

Last update: VISEK (14.04.2008)