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REPORT The 22nd Didactic Conference on Teaching Quality Evaluation Methods,10-11 June 2013, Łódź, Poland

100%
Kupis-Fijałkowska A.
Statistics in Transition new series
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2013
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vol. 14
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issue 2
337-340
2
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Introduction

63%
Domański C., Kupis-Fijałkowska A., University of Lodz D. o. S. M., University of Lodz D. o. S. M.
Acta Universitatis Lodziensis. Folia Oeconomica
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2013
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vol. 285
3
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The XXXI International Conference on Multivariate Statistical Analysis, 12–14 November 2012, Łódź, Poland

63%
Mikulec A., Kupis-Fijałkowska A.
Statistics in Transition new series
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2012
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vol. 13
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issue 3
611-616
4
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Efekty kształcenia w szkolnictwie wyższym i problem ich ewaluacji w polskim ustawodawstwie

63%
Kupis-Fijałkowska A., Janas K., Uniwersytet Łódzki I. S. i. D.
Acta Universitatis Lodziensis. Folia Oeconomica
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2013
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vol. 280
EN
The paper aims to discuss the legal and regulatory aspects of the assessment of learning outcomes for the higher education level. A particular attention is paid to the National Qualifications Framework in Poland, which aims to implement transparency in the competencies formulation process and enable to compare skills of graduates of various universities throughout Europe. Authors emphasize a problem of the legal failure in defining methods for measuring and assessing the quality of learning outcomes, although it is postulated that the National Qualifications Framework for higher education is a tool for education quality improvement.
5
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An Empirical Analysis of the Effectiveness of Wishart and Mojena Criteria in Cluster Analysis

63%
Mikulec A., Kupis-Fijałkowska A.
Statistics in Transition new series
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2012
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vol. 13
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issue 3
569-580
EN
Mojena and Wishart criteria are methods of selecting the optimal grouping result of agglomerative cluster analysis methods (hierarchical). Two criteria were proposed by Mojena in the 70’s of the 20th century: the upper tail rule and moving average quality control rule, both based on an analysis of the fusion levels of objects in the dendrogram with the aim to determine the cut-off point of it, i.e. to choose the optimal clustering result. The third criterion: tree validation was created by Wishart and evaluates the randomness of the objects clustering in the dendrogram. The purpose of this paper is to present the results of the empirical analysis of the effectiveness of Mojena and Wishart criteria for the number of clusters selection, in comparison to other applicable criteria in this area, including those proposed by: Baker and Hubert, Calinski and Harabasz, Davies and Bouldin, Hubert and Levine. The empirical analysis has been carried out in ClustanGraphics 8 Program and selected packages in R environment for the generated data sets.
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