Statistics

Basic Information

M120 (2+2+1) - 6 ECTS credits

Understanding mathematical statistics methods and training them to apply these methods to data analysis.

 

You can access the course content at the following link: PDF

Teachers

Basic literature

  1. L. E. Bain and M. Engelhardt – Introduction to Probability and Mathematical statistics, BROOKS/COLE Cengage Learning, 1992.

Additional literature

  1. R. Pruim, Foundations and Applications of Statistics. An Introduction Using R, AMS, Providence, Rhode Island, 2018.
  2. J.A. Rice, Mathematical Statistics and Data Analysis, Brooks/Cole, Cengage Learning, 2007.
  3. M. J. Crawley, The R Book, J. Wiley & Sons, 2007.
  4. K. Knight, Mathematical Statistics, Chapman & Hall/CRC, Boca Raton-Washington, 1999.
  5. R. C. Mittelhammer, Mathematical statistics for economics and business, Springer, 1996.
  6. E. L. Lehman, Elements of Large-Sample Theory, Springer, 1999.
  7. E. L. Lehman, G. Casella, Theory of Point Estimation, Springer, 1998.
  8. J. E. Freund, Mathematical Statistics, Prentice Hall, 1992.

Teaching materials

The materials are available on the internal Teams channel of the course, through which all internal communication takes place. Students are required to register on the course’s Teams channel. The channel code for joining the course can be found in the schedule.