Advanced statistical methods for data analysis

Type of study	Doctoral
Language of instruction	Czech
Code	151-0901/01
Abbreviation	PMSAD
Course title	Advanced statistical methods for data analysis
Credits	10
Coordinating department	Department of Mathematical Methods in Economics
Course coordinator	doc. Ing. Václav Friedrich, Ph.D.

Subject syllabus

1. Analysis of variance; one-way design, contrasts, post hoc tests, two-way design, a model with interactions.
2. Categorical data analysis; contingency tables, logistic regression, estimating the logistic regression model, interpreting the coefficients, assessing the googness-of-fit of the estimation model.
3.Unidimensional scaling; approaches to scaling, order scaling, Likert scaling, Guttman scaling, comparative judgment – Thurstone scaling.
4. Factor analysis; determining the dimensions of correlation, latent and manifest variables, extracting the principal solution, importance and interpretation of factors, rotating the factors, additional uses of factor analysis results.
5. Cluster analysis; principles, determining similarity, methods.
6. Statistical quality control; methods and philosophy of statistical process control, control charts, acceptance-sampling problem.

Literature

ANDERSON, David Ray, Dennis J. SWEENEY a Thomas Arthur WILLIAMS. Statistics for business and economics. 11th ed., rev. Mason: South-Western Cengage Learning, c2012. ISBN 978-0-538-48164-9.
TABACHNICK, Barbara G. a Linda S. FIDELL. Using multivariate statistics. 5th ed. Boston: Pearson Allyn & Bacon, c2007. ISBN 978-0-205-45938-4.
MONTGOMERY, C.M. Introduction to Statistical Quality Control. John Wiley & Sons, 2009. 734 p. ISBN 978-0-470-16992-6.

Advised literature

WEISBERG, Sanford. Applied linear regression. 4th ed. Hoboken: Wiley, c2014. Wiley series in probability and statistics. ISBN 978-1-118-38608-8.
GAMST, G., MEYERS, L.S. and GUARINO, A.J. Analysis of Variance Designs. Cambridge University Press, 2008. 578 p. ISBN 978-0-521-87481-6.
AGRESTI, Alan. Foundations of linear and generalized linear models. Hoboken: Wiley, [2015]. Wiley series in probability and statistics. ISBN 978-1-118-73003-4.

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