@misc{Blatná_Dagmar_European_2009,
 author={Blatná, Dagmar},
 year={2009},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Publishing House of Wrocław University of Economics},
 description={Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2009; Nr 66, s. 21-31},
 language={eng},
 abstract={European countries can be characterized by indicators of general economic background, employment, innovation and research, science and technology. Values of these indicators are varying among European countries. The most used statistical tool for analyzing dependences is the regression analysis. The classical statistical approach - the least squares method (LS) may be highly unsatisfactory in the presence of outliers which can be supposed in analysis of European countries data. In such a case robust regression is acceptable and useful tool. The paper proves that the estimates of regression coefficients obtained by using a robust regression method can be significantly different from the ones obtained in the case of classical regression. The differences in results are significant namely in the cases where outliers and leverage points are identified. Some regression models suitable both from the point of view of goodness-of-fit test and satisfying t-tests and chi-square tests for individual parameters of regression models for Labour productivity per person employed are presented.},
 title={European Countries Analysis Using Robust Regression Methods},
 type={artykuł},
}