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Methods of Regional Analysis

Course developer

Course abstract

Subject imparts knowledges about elements of theoretical and methodical regional research in depth, methods of data yield, methods of data analysis and its application for regional data.

Learning outcomes and their assessment

Upon successful completion of this course:
1. Students acquire in-depth knowledge and critical understanding of the latest theoretical and methodical bases of regional research, methods of data collection and analysis which provide the basis for creative thinking in the regional economy. - tests
2. students are able to self-formulate, critically analyse problems in the regional economy, choose appropriate regional methods of analysis, be able to explain and debate in a reasoned way the understanding of relevant concepts and laws, to perform necessary caluculations and operations. Students are able to use appropriate software for calculations. - practical and laboratory work
3. Working in a group or doing work independently, student is able to apply the regional analysis methods corresponding to the specialty problem situation, to make a professional assessment and interpretation of the intermediate and the final results. Student is able to self-direct the development and specialisation of his/her skills, integrate regional methods of analysis into the creation of new knowledge, contribute to the development of research and professional activities – independent studies

Course Content(Calendar)

1. Regional Development Policy in the EU and Latvia. Regionalisation processes in the EU. The newest legal and regulatory framework for the regional economy. (2 h)
2. Preparing data for analysis. Working with large array of output data. (2 h)
3. Testing hypotheses in correlation analysis. Studying the closeness of relationships. Linear and non-linear correlation. Positive and negative correlation. Pairing and multifactor correlation. Covariance. Examples in the regional economy. Adoption of the decision and interpretation of the results. (5 h)
4. ng hypotheses in regression analysis. Determination and use of the regression model. Regression zone. The area of the average forecast. The area of the individual forecast. Verification of regression pattern assumptions. Multi-factor linear regression. Testing hypotheses. Non-linear regression. Select the corresponding regression model. Examples in the regional economy. Adoption of the decision and interpretation of the results. (6 h)
Test 1.. Correlation. Regression.
5. Analysis of dynamic time series. Establishment and evaluation of trendland. Assessment of the quality of equalisation. Examples in the regional economy. Adoption of the decision and interpretation of the results. (4 h)
6. Parametric and non-parametric data processing methods. Nature of parametric and non-parametric methods, conditions of use. 2 criterion. Verification of the empirical distribution. 2 criterion for verifying the conformity of qualitative samples. 2 criterion as a test for statistical independence. Examples in the regional economy. Adoption of the decision and interpretation of the results.) (3 h)
7. Parametric and non-parametric methods of analysis of two samples. Independent and related samples. t-tests. F-test. Mann-Whitney U test. Colmogorov - Smirnov method. Wilcoxon test. Mark test. Examples in the regional economy. Adoption of the decision and interpretation of the results. (3 h)
8. Parametric and non-parametric methods for multi-sample analysis. Analysis of variance. Single-factor analysis of variance. Two-factor analysis of variance with and without replication. Kruskal — Valis test. Medias test. Friedman test. Examples in the regional economy. Adoption of the decision and interpretation of the results. (3 h)
9. Classification and grouping. Selection of factors. Methods of analysis of cluster. Standardisation of data. Dendogram. Quick cluster. K-mean method. Interpretation of the results of the cluster analysis. (2 h)
Test 2.. Analysis of dynamic time series. 2 criterion. Parametric and non-parametric analysis methods.

Requirements for awarding credit points

Examination

The course is completed without additional knowledge examination if the results of the semester are summarized as 2 successful written tests (average grade at least 4).
There is 1 independent home work in the semester (submitted in writing, orally presented).

Description of the organization and tasks of students’ independent work

Tasks for the independent work are included in e-studies every week.
There is 1 independent home work (in writing) in the semester.

Criteria for Evaluating Learning Outcomes

During the semester 2 tests, each scored with a maximum of 8.
One option is given to write a test. For an justified reason, the test may be written in the another time.
The final assessment depends on the cumulative assessment of the semester:
• successful average grade of two practical tests (maximum of 8);
• 1 independent home work (orally presented, maximum of 2).
In the case of unsuccessful co-score of two tests (below 4), the student shall be responsible for the whole study material in the individual study and testing period.

Compulsory reading

1. Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā. Rīga: Datorzinību Centrs, 2006. 364 lpp.
2. Grīnglazs L., Kopitovs J. Matemātiskā statistika: ar datoru lietojuma paraugiem uzdevumu risināšanai. Rīga: RSEBA, 2003. 310lpp.
3. Ekonomisko pētījumu metodes un informācijas avoti: mācību līdzeklis. Sast. V.Kozlinskis. Jelgava: LLU, 2001. 66 lpp.
4. Paura L., Arhipova I. Neparametriskas metodes. SPSS datorprogramma. Mācību līdzeklis. Jelgava: LLKC, 2002. 148 lpp.

Further reading

1. Dažādā Latvija: pagasti, novadi, pilsētas, rajoni, reģioni. Vērtējumi, perspektīvas, vīzijas. Rīga: Latvijas Statistikas institūts. Valsts reģionālās attīstības aģentūra, 2004. 539 lpp.
2. Berenson M.L., Levine D.M. Basic Business Statistics. Concepts and Applications. USA: PrenticeHall, 2009. 1013 p.
3. Vanags E., Vilka I. Pašvaldību darbība un attīstība. Rīga : Latvijas Universitātes Akadēmiskais apgāds, 2005. 384 lpp.

Periodicals and other sources

1. LR Centrālās statistikas pārvalde. Statistisko datu krājumi.
2. www.csb.lvPašvaldību darbība un attīstība

Notes

Restricted elective course for Master’s study programme “Economics”