Ranking e valutazione: il caso delle classifiche delle universitŕ

2009 ◽  
pp. 81-114
Author(s):  
Ferruccio Biolcati Rinaldi ◽  
Daniele Checchi ◽  
Chiara Guglielmetti ◽  
Silvia Salini ◽  
Matteo Turri
Keyword(s):  
Cluster Analysis ◽  
Key Words ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Partial Replication ◽  
Validity And Reliability ◽  
University Ranking ◽  
International Ranking ◽  
Components Analysis ◽  
And Cluster Analysis

- Abstract The paper consists of two parts. The first is more general: it introduces to university ranking, shows the leading international ranking, discusses the uses people make of rankings. The second focuses on Italian ranking Censis-la Repubblica developing two different kinds of analyses: after considering indicators validity and reliability, principal components analysis and cluster analysis are applied to a partial replication of Censis-la Repubblica data. A list of points to pay attention comes out of these analyses: it can be useful when defining rankings of complex institutions such as universities.Key words: ranking, university ranking, Censis-la Repubblica, validity and reliability, normalisation and combination of indicators.

Characterization of Isometric Limb Muscle Strength of Older Adults

2000 ◽  
Vol 8 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Richard W. Bohannon ◽  
A. Williams Andrews
Keyword(s):  
Cluster Analysis ◽  
Muscle Strength ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Elbow Flexion ◽  
The Elderly ◽  
Limb Muscle ◽  
Components Analysis ◽  
And Cluster Analysis ◽  
Muscle Actions

Overall muscle strength of extremities is often characterized by measurements from one or more selected actions. This study evaluated the legitimacy of that procedure. Measurements obtained by handheld dynamometry from 13 muscle actions of 156 apparently healthy individuals (50–79 years) were subjected to correlational analysis, principal-components analysis, and cluster analysis. The isometric strengths of all muscle actions correlated significantly with one another (r = .506–.965). Principal-components analysis without rotation showed that all tested actions loaded highly on overall limb muscle strength. Principal-componcnis analysis with varimax rotation revealed high loadings that were grouped by extremity (upper vs. lower). Ankle dorsiflexion strengths were exceptions. These findings, in conjunction with the cluster analysis, support using one or more actions to characterize isometric limb muscle strength among the elderly but suggest that muscle strength in an upper or lower extremity is best characterized by an action (e.g., elbow flexion) of that extremity.

scholarly journals Diagnostic Petiole Anatomical Characters and their Systematc Importance in eighteen (18) species of the genus Tephrosia PERS (fabaceae) found in Nigeria

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Omoteso Oluwa ◽  
Dele Olowokudejo ◽  
Oluwatoyin Ogundipe
Keyword(s):  
Cluster Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Statistical Treatment ◽  
Systematic Investigation ◽  
Data Matrix ◽  
Anatomical Characters ◽  
Components Analysis ◽  
And Cluster Analysis

A comprehensive systematic investigation on diagnostic petiole characters of eighteen species of Tephrosia, from family Fabaceae, tribe Milleteae. It habits the fringes often forests, and abandoned, and wastelands. A total of nine diagnostic polymorphic characters were observed, photographed, assessed,scoredand coded as Data matrix for quantitative statistical treatment. The 9 characters codes include PSY, POL, PVS, PPT, and PTE. others include PTA, PTO, PTC, and PTB. Principal Components Analysis (PC) and Cluster Analysis were carried out. Four PC were identified and Cluster analysis indicates twelve hierarchies.

Chemistry research in Europe: A publication analysis (2006–2016)

2019 ◽  
pp. 016555151986549
Author(s):  
Hakan Kaygusuz
Keyword(s):  
Cluster Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Polymer Science ◽  
Chemistry Research ◽  
Research Outcome ◽  
Components Analysis ◽  
Number Of Publications

In this article, chemistry research in 51 different European countries between years 2006 and 2016 was studied using statistical methods. This study consists of two parts: In the first part, different economical, institutional and citation parameters were correlated with the number of publications, citations and chemical industry numbers using principal components analysis and hierarchical cluster analysis. The results of the first part indicated that economical and geographical parameters directly affect the chemistry research outcome. In the second part, research in branches of chemistry and related disciplines such as analytical chemistry, polymer science and physical chemistry were analysed using principal components analysis and hierarchical cluster analysis for each country. Publication data were collected as the number of chemistry publications (in Science Citation Index–Expanded (SCI-E)) between years 2006 and 2016 in different chemistry subdisciplines and related scientific areas. Results of the second part of the study produced geographical and economical clusters of countries, interestingly, without addition of any geographical data.

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