1. Statistical Data Analysis Informatics, autumn term 2008/2009

2. Tomáš Hlavsa PEF 427, department of statistics E-mailhlavsa@pef.czu.cz Office hoursMon, Wed 2 – 3 p. m. Webhttp://pef.czu.cz/~hlavsa

3. Statistical Data Analysis courses Lectures Tue 5.30 – 7 p. m. Practicals Tue 7.15 – 8 p. m. Credit – will be granted on the condition of the presentation and project in its written form Examination – written and oral (theory and computation problems)

4. Project Analysis of the state and development of the human capital in regions Topics Demographic development Economic structure of inhabitans Unemployment Living standard of inhabitants Social level of inhabitants Health state of inhabitants

5. Project working groups (3 students) presentation at practicals from October 14th (three parts) –1st presentation (region describing, selection of variable, univariate analysis) (14. 10. and 21. 10.) –2nd presentation (development tendencies in region, average change coefficient, time series, graphical comparison, evaluation) (4. 11. and 11. 11.) –3rd presentation (results of the PCA and CA) (18. 11. and 25. 11) written form (1st, 2nd, 3rd part, conclusions of the results) (last week in the autumn term)

6. Project – parts Introduction –intro to the human capital problems, why is needed to analyse it Methodology –write step by step the procedure of your work –describe used methods Results –results from the statistical analyses Conclusions –conclusions from the analyses, recommendation

7. Project evaluation of the chosen indicators by elementary statistical methods (mean, variation, extrems, etc.) describing of development in time (average change) time series analysis, forcasting of the chosen indicators detecting of structure and relationship among variables detecting of factors, which have the biggest effect on human capital in regions reduction of the large number of variables to a small number of new variables creation of aggregate composite indicators for each part of the regional development creation of groups of regions with similar development

8. Example Pardubický region (kraj, NUTS 3) –Pardubice county (okres, NUTS 4) –Chrudim county (okres, NUTS 4) –Svitavy county (okres, NUTS 4) –Ústí nad Orlicí county (okres, NUTS 4) describing and comparison of chosen variables –unemployment, share of population between 14 – 65 years, average wage….. – univariate analysis

9. Project – presentation Nr. 1 choice of region at level NUTS 3 (kraj) and its counties NUTS 4 (okres) selection of variables (min length of period is 2003 – 2006) univariate analysis (mean, variation, comparison) presentation in ppt form send per e-mail till 13. 10., 2 p. m. data source: Czech statistical office, Regional yearbooks (Regions, towns,…), www.czso.cz, other sources (ministry of labour etc.)www.czso.cz

10. Your background for succesfull beginning of SDA Statistical knowledges at bachelor level –statistical description: basic measures of the univariate statistics (mean, variation) –statistical inference sample estatimation (point estamates, confidence intervals for mean, variance, rel frequencies) statistical hypothesis testing (parametric and non parametric methods; par: one sample tests, two sample tests, ANOVA; non par: Wilcoxon White, Wilcoxon, Kruskal Wallis) –regression and correlation analysis (simple, multivariate, linear, non linear; + parameters testing and testing of whole model)

11. Your background for succesfull beginning of SDA –time series descripting and forecasting (trend, seasonal fluctuation) –analysis of crosstabulation (analysis of contingency and association, testing) user skills of SAS (or Statistica by StafSoft?)

12. Basic terminology population sample data types –qualitative (nominal, ordinal) –quantitative (descrete, continuous) distribution

13. Basic terminology mean (střední hodnota) –average (průměr) from individual values x from frequency distribution –mode (modus) –median (medián) variation (variabilita) –standard deviation (směrodatná odchylka) s –variance (rozptyl)s 2 from individual values x from frequency distribution –coefficient of variationv