Statistics 2
Code  Completion  Credits  Range  Language 

U63C4101  Z,ZK  6  2P+2C  Czech 
 Relations:
 It is not possible to register for the course U63C4101 if the student is concurrently registered for or has previously completed the course 32BCPSTA201 (mutually exclusive courses).
 The requirement for course U63C4101 can be fulfilled by substitution with the course 32BCPSTA201.
 Course guarantor:
 Lecturer:
 Tutor:
 Supervisor:
 Institute of Economic Studies
 Synopsis:

The course develops on the Statistics I themes; students will receive an extension basic principles of statistical knowledge, which they have acquired during the study Statistics I. Deepening relates to the field of random variables  random vector field and nonparametric testing. The other topics below mentioned is extending the knowledge acquired in previous Statistics I course. After completing the course, students will be ready to use the complicated methodological apparatus suitable for extraction of knowledge from both quantitative and qualitative data files.
 Requirements:

Entrance requirements are composition of the exam from Statistics 1, Mathematics 1, Mathematics 2.
 Syllabus of lectures:

The course develops on the Statistics I themes; students will receive an extension basic principles of statistical knowledge, which they have acquired during the study Statistics I. Deepening relates to the field of random variables  random vector field and nonparametric testing. The other topics below mentioned is extending the knowledge acquired in previous Statistics I course. After completing the course, students will be ready to use the complicated methodological apparatus suitable for extraction of knowledge from both quantitative and qualitative data files.
. Random vector, distribution and frequency functions of a random vector.
. Independence of random vector components, marginal probability distribution.
. Numerical characteristics of a random vector, conditional distribution of probability.
. Statistical induction and random selection.
. Maximum reliability method, point and interval estimates of parameters, determination of the range of random selection.
. Normality tests (AndersonDarling test, Test of a good agreement, ShapiroWilks test, KolmogorovSmirnov test).
. Graphic analysis, Boxplot, histogram.
. Nonparametric testing of statistical hypotheses, singlechoice and doublechoice Wilcoxon test, twosample KolmogorovSmirnov test.
. General analysis of categorical data, evaluation of frequencies, comparison of the relative frequency with the theoretical value.
. Analysis of dependencies of nominal and ordinal data type, pivot table, hypothesis testing of independence.
. Measurement of dependence force of nominal type quantities. Quadruple (association) table and independence testing in the fourpane table.
. Statistical metaanalysis, homogeneity test, aggregation of effect size, encoding of information.
. Methods of multidimensional analysis, external analysis, internal analysis (analysis of main components, factor analysis, cluster analysis).
. Logistic regression, dependency modeling using regression trees.
. Selection of statistical methods, classification of statistical methods, problems of significance tests, Bayesian approach, computationally intensive methods.
 Syllabus of tutorials:

. The course develops on the Statistics I themes; students will receive an extension basic principles of statistical knowledge, which they have acquired during the study Statistics I. Deepening relates to the field of random variables  random vector field and nonparametric testing. The other topics below mentioned is extending the knowledge acquired in previous Statistics I course. After completing the course, students will be ready to use the complicated methodological apparatus suitable for extraction of knowledge from both quantitative and qualitative data files.
. Random vector, distribution and frequency functions of a random vector.
. Independence of random vector components, marginal probability distribution.
. Numerical characteristics of a random vector, conditional distribution of probability.
. Statistical induction and random selection.
. Maximum reliability method, point and interval estimates of parameters, determination of the range of random selection.
. Normality tests (AndersonDarling test, Test of a good agreement, ShapiroWilks test, KolmogorovSmirnov test).
. Graphic analysis, Boxplot, histogram.
. Nonparametric testing of statistical hypotheses, singlechoice and doublechoice Wilcoxon test, twosample KolmogorovSmirnov test.
. General analysis of categorical data, evaluation of frequencies, comparison of the relative frequency with the theoretical value.
. Analysis of dependencies of nominal and ordinal data type, pivot table, hypothesis testing of independence.
. Measurement of dependence force of nominal type quantities. Quadruple (association) table and independence testing in the fourpane table.
. Statistical metaanalysis, homogeneity test, aggregation of effect size, encoding of information.
. Methods of multidimensional analysis, external analysis, internal analysis (analysis of main components, factor analysis, cluster analysis).
. Logistic regression, dependency modeling using regression trees.
. Selection of statistical methods, classification of statistical methods, problems of significance tests, Bayesian approach, computationally intensive methods.
 Study Objective:

The primary course objective is to create a followup methodological framework for the use of advanced stochastic methods (based on probability distribution of random variables) to enable students to sophistically analyze and regulate residuals of economic phenomena and business management processes.
 Study materials:

OBLIGATORY
Freedman D. (2007). Statistics, Third Edition. Norton & Company, Incorporated, W. W.ISBN13: 9780393970838
RECOMMENDED
Kutner, M., Nachtsheim, C., Neter, J., and Li, W. (2004). Applied Linear Statistical Models, McGrawHill/Irwin, Homewood, IL.
LIND, D., MARCHAL, W., WATHEN, S. (2015) Statistical Techniques in Business and Economics, (16th Edition). McGrawHill Education. ISBN13: 9780078020520.
TRIOLA, M., F. Essentials of Statistics (5th Edition). Pearson Education 2015. ISBN13: 9780321924599.
Tufte, E. R. (2001). The Visual Display of Quantitative Information (2nd ed.) (p.178). Cheshire, CT: Graphics Press
 Note:
 Further information:
 https://idp2.civ.cvut.cz/idp/profile/SAML2/Redirect/SSO?execution=e3s1
 No timetable has been prepared for this course
 The course is a part of the following study plans:

 BEKprez.forma od 15/16 (compulsory course)
 BPMprez.forma od 15/16 (compulsory course)
 BEKprez.forma od 16/17 (compulsory course)
 BEKprez.forma od 17/18 (compulsory course)
 BEMP prezenční studium od 18/19 (compulsory course)
 BEMP prezenční studium od 19/20 (compulsory course)
 BEMP prezenční studium od 20/21 (compulsory course)
 BEMP prezenční studium od 21/22 (compulsory course)
 BEMP prezenční studium od 22/23 (compulsory course)