151-0352/01 – Correlation and Regression Analysis (KRA)

Gurantor departmentDepartment of Mathematical Methods in EconomicsCredits4
Subject guarantorprof. Ing. Jana Hančlová, CSc.Subject version guarantorprof. Ing. Jana Hančlová, CSc.
Study levelundergraduate or graduate
Study languageCzech
Year of introduction2010/2011Year of cancellation2012/2013
Intended for the facultiesEKFIntended for study typesBachelor, Follow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
HAN60 prof. Ing. Jana Hančlová, CSc.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 1+2

Subject aims expressed by acquired skills and competences

The goal is to: - Be able to examine the relationship between variables, - Understand the process of modeling the behavior of economic systems based on regression analysis, - Select and use appropriate methods to the formulation, estimation, prediction and verification of modeled systems, - Explain the behavior of the theoretical context of economic systems modeled with empirical results and make appropriate modifications and corrections model - Use the estimated regression models to predict and determine the success of prediction, - Learn how to use SPSS software product for regression and correlation analysis.

Teaching methods

Lectures
Tutorials
Other activities

Summary

1. Pearson's correlation coefficient - the characteristics, correlation and covariance, correlation and causality. 2. The serial correlation coefficients, correlations for dichotomous variables, testing hypotheses about the significance of coefficients, tests of equality of two coefficients. 3. The correlation matrix, partial correlation and its significance. 4. Correlation and linear regression equation (straight line), features a simple linear regression, principle of the method of least squares. 5. Hypothesis testing and parameter estimation of the regression straight line coefficient determination, residues and their analysis. 6. Nonlinear regression and be transformed into a linear regression model. 7. Prediction of the regression equation. 8. Multiple linear regression model, significance of regression coefficients, test of significance of regression coefficients.

Compulsory literature:

• Hindls, R. - Hronová, S. - Seger, J. - Fisher, J. Statistika pro ekonomy. 8. vyd. Praha: Professional Publishing, 2007. 417 s. ISBN 978-80-86946-43-6. • Hušek, R. Ekonometrická analýza. 1. vydání. Praha: VŠE, 2007. ISBN 978-80-245-1300-3. • Lukáčiková, A., Lukáčik, M. Ekonometrické modelovanie s aplikáciami. BRATISLAVA: EKONÓM, 2008. ISBN-978-80-225-2614-2.

Recommended literature:

• Gujarati, D. N.: Basic Econometrics, 4. Ed., Mc Graw-Hill, Singapore, 2003. ISBN 0-07-233542-4. • Marek, L. Statistika v SPSS – časové řady. Praha: VŠE, 1995, ISBN 80-7079-642-1.

Way of continuous check of knowledge in the course of semester

1. Preparation and submission of homework. 2. Successful completion of ongoing testu1. 3. Successful completion of the final testu2. Deadlines for submission of homework and deadlines and testu1 testu2 timetable are given subject. Each test is possible to repeat once again. Successful completion is achieved at least half the possible points in each test and assignment.

E-learning

http://moodle.vsb.cz/

Další požadavky na studenta

not *******************************

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Pearson's correlation coefficient - the characteristics, correlation and covariance, correlation and causality. 2. The serial correlation coefficients, correlations for dichotomous variables, testing hypotheses about the significance of coefficients, tests of equality of two coefficients. 3. The correlation matrix, partial correlation and its significance. 4. Correlation and linear regression equation (straight line), features a simple linear regression, principle of the method of least squares. 5. Hypothesis testing and parameter estimation of the regression straight line coefficient determination, residues and their analysis. 6. Nonlinear regression and be transformed into a linear regression model. 7. Prediction of the regression equation. 8. Multiple linear regression model, significance of regression coefficients, test of significance of regression coefficients.

Conditions for subject completion

Full-time form (validity from: 2010/2011 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Exercises evaluation Credit 85 (18) 85
        Test_1 Written test 9  5
        Test_2 Written test 9  5
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2011/2012 (B6202) Economic Policy and Administration (6202R040) Regional Development P Czech Ostrava Choice-compulsory study plan
2010/2011 (N6208) Economics and Management (6208T020) Business Economics (00) Business Economics P Czech Ostrava 1 Choice-compulsory study plan
2010/2011 (B6202) Economic Policy and Administration (6202R040) Regional Development P Czech Ostrava 2 Choice-compulsory study plan
2010/2011 (N6202) Economic Policy and Administration (6202T040) Regional Development (00) Regional Development P Czech Ostrava 1 Choice-compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner