Pasha Zusmanovich - teaching

A.T. Fomenko, Geometry and Probability,
Ink and pencil on paper, 38 x 47.5 cm, 1987

VAPMS Selected Applications of Mathematical Statistics, summer semester 2018/2019

Approximate syllabus:

The subject of statistics. Types of data.
Basic notions of descriptive statistics: mean, median, mode, quantiles, standard deviation.
Correlation, correlation matrices.
Normal distribution. Confidence interval.
Various types of distributions.
Null and alternative hypotheses. Hypothesis testing.
Statistical models. Linear regression. Least squares.
Clustering.
Working with R.

A very brief synopsis:

A parallel Czech-English text covering some of the topics in probablity and statistics is available on the page of Introduction to Probability & Statistics course.

Literature:

J. Albert and M. Rizzo, R by Example, Springer, 2012. [OU library]
C.-H. Chen, Generalized association plots: information visualization via iterative generated correlation matrices, Statistica Sinica 12 (2002), 7-29.
Y. Cohen and J.Y. Cohen, Statistics and Data with R, Wiley, 2008. [OU library]
M.J. Crawley, Statistics: An Introduction Using R, 2nd ed., Wiley, 2014. [OU library (1st edition)]
M.J. Crawley, The R Book, 2nd ed., Wiley, 2013. [OU library]
P. Dalgaard, Introductory Statistics with R, 2nd ed., Springer, 2008. [OU library]
B.S. Everitt and T. Hothorn, A Handbook of Statistical Analyses Using R, 2nd ed., Chapman & Hall/CRC, 2010. [OU library (1st edition)]
L. Gonick and W. Smith, The Cartoon Guide to Statistics, HarperPerennial, 1993. [OU library]
Handbook of Statistics. Volume 32. Computational Statistics with R (ed. M.B. Rao and C.R. Rao), Elsevier, 2014.
J. Maindonald and W.J. Braun, Data Analysis and Graphics Using R, 3rd ed., Cambridge Univ. Press, 2010. [OU library (2nd edition)]
L. Pace, Beginning R. An Introduction to Statistical Programming, Apress, 2012.
R. Pruim, Foundations and Applications of Statistics. An Introduction Using R, 2nd ed., AMS, 2018. [OU library]
W.N. Venables, D.M. Smith et al., An Introduction to R, 2015. [online pdf] [online HTML] [OU library (old edition)]
J. Verzani, Using R for Introductory Statistics, 2nd ed., Chapman & Hall/CRC, 2014. [OU library (1st edition)].

All the books are available in electronic form in multiple places.

Online sources:

R Programming, Wikibook.
Stack Exchange sites: stackoverflow and Cross Validated.

Software: R
Code used in the classes: [Class 1] [Class 2] [Class 3] [Class 4] [Class 5] [Class 6] [Class 7] [Class 8] [Class 9]

Homeworks
Unless specified otherwise, the homeworks have to be submitted by email, one homework per email. In the subject, please indicate the number of the homework. All R code should be submitted as an attachment in one of two forms: either as a plain text file ready to be loaded to R, or as a saved R workspace. If the homework involves analysis of a dataset of your choice, do not forget to supply the dataset itself, or clearly indicate its origin -- for example, dataset from R or from internet. Be descriptive -- supply not only the R code, but explanations of what and why you are doing. Points awarded for homeworks are counted toward your final credit (to successfully pass the course, one should accumulate at least 20 points). All homeworks/emails can be written in English or Czech.

Created: Wed Sep 23 2015
Last modified: Sat Sep 18 11:26:50 Central Europe Daylight Time 2021