STATISTICAL STUDIES ON SCAPOLITES

1964 ◽  
Vol 1 (1) ◽  
pp. 23-34 ◽  
Author(s):  
Gerard V. Middleton
Keyword(s):  
Solid Solution ◽  
Factor Analysis ◽  
Trace Element ◽  
Statistical Techniques ◽  
Trace Element Data ◽  
Multivariate Statistical Techniques ◽  
Factor Analyses ◽  
Multivariate Statistical ◽  
Element Data ◽  
Statistical Studies

The multivariate statistical techniques of component and factor analyses, when applied to major and trace element data presented by Shaw (1960), identify the Marialite–Meionite solid solution in scapolites and tentatively suggest the existence of an independent end-member bearing Mg and (OH). Three trace element factors suggest the groupings[Formula: see text]It is suggested that factor analysis may be a useful technique to apply to other complex mineral groups.

scholarly journals Micro-SME Characterization From Financial Statements

2012 ◽  
Vol 11 (13) ◽  
pp. 1507
Author(s):  
Guillermo Ceballos-Santamaria ◽  
Juan-Jose Villanueva-Alvaro ◽  
Jose Mondejar-Jimenez
Keyword(s):  
Factor Analysis ◽  
Statistical Analysis ◽  
Small Businesses ◽  
Financial Statements ◽  
Developed Countries ◽  
Financial Statement ◽  
Statistical Techniques ◽  
General Interest ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical

In recent years, small businesses have created interest and research, because they represent the majority of the business fabric and account for over seventy per cent of jobs in developed countries. Governments of these countries share a general interest in knowing about Small and Medium-Sized Enterprises (SME). Based on this premise, the approach of this study is to characterize micro-SMEs in the province of Cuenca, Spain, by analysis of financial statements, specifically analyzing their structure in financial terms by use of univariate and multivariate statistical techniques allowing this kind of business in the province of Cuenca to be identified. The information used comes from the databases of SABI (Iberian Financial Statement Analysis Systems), DIRCE (Central Business Directory and CamerData, the database of the Chambers of Commerce. The statistical analysis is centered on a classic modal of exploratory factor analysis, and finally the main results arising from the study are presented.

Multivariate Statistical Analysis of a Regional Subsistence-Settlement Model for Owens Valley

1979 ◽  
Vol 44 (3) ◽  
pp. 455-470 ◽  
Author(s):  
Robert L. Bettinger
Keyword(s):  
Factor Analysis ◽  
Statistical Analysis ◽  
Discriminant Analysis ◽  
Human Ecology ◽  
Multivariate Statistical Analysis ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Owens Valley ◽  
Multivariate Statistical

Despite their growing importance in the study of prehistoric human ecology, regional subsistence-settlement models continue to be developed and justified largely on intuitive grounds. This shortcoming can be at least partially overcome by using multivariate statistical techniques to clarify and refine these models. Such an approach is illustrated using classical factor analysis and discriminant analysis to explicate and improve a regional subsistence-settlement model previously developed for Owens Valley, eastern California.

scholarly journals HOW DO BRAZILIANS PERCEIVE FOOD WASTE?

2021 ◽  
Vol 14 (3) ◽  
pp. 246-260
Author(s):  
Giana De Vargas Mores ◽  
Leila Dal Moro ◽  
Yasmin Gomes Casagranda ◽  
Vitor Francisco Dalla Corte ◽  
Gabriele Girardi
Keyword(s):  
Factor Analysis ◽  
Food Waste ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
The Public ◽  
Factors Associated ◽  
Five Factors ◽  
Relevant Topic ◽  
Self Administered Questionnaire

This research aims to identify the profile and factors associated with the perception of Brazilianconsumers regarding food waste. The chosen technique was survey research, with the application ofa structured online and self-administered questionnaire with 664 Brazilian consumers. Descriptivestatistics were calculated and multivariate statistical techniques, such as factor analysis and multiplelinear regression. Five factors have different affirmations on assessing and dealing with the food,besides the behavior concerning food and its respective waste. The factor regarding education wasincluded in the survey, adapted from Richter (2017), which generated this factor. This is an additionalresult when applied to the Brazilian context. The waste is associated with behavioral factors. One ofthe main contributions was to present the use of metrics, which provide comparisons betweendifferent themes of food waste, providing proposals for the public policies and guidelines forminimizing this problem. The study helps with discussions based on a relevant topic for humanity andcontemplating the UN SDGs through a national diagnosis. Academics, public, private, and non-profitorganizations have increasingly brought the spotlight onto food waste. Implications of this study pointto the need for effective policies turned to mitigate food waste.

scholarly journals Assessment of Tigris River Water Quality Using Multivariate Statistical Techniques

2019 ◽  
Vol 26 (4) ◽  
pp. 26-31
Author(s):  
Muntasir Shareef
Keyword(s):  
Water Quality ◽  
Factor Analysis ◽  
Total Variance ◽  
Quality Data ◽  
Statistical Techniques ◽  
Complex Nature ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Water Quality Data ◽  
Tigris River

The present study uses the multivariate statistical techniques by applying the Factor Analysis (Principle component method) to explain the observed water quality data of Tigris river within Baghdad city. The water quality was analyzed at eleven different sites, along the river, over a period of one year (2017) using 20 water quality parameters. Five factors were identified by factor analysis which was responsible from the 72.291% of the total variance of the water quality in the Tigris river. The first factor called the pollution factor explained 34.387% of the total variance and the second factor called the surface runoff and erosion factor explained 11.875% of the total variance. While, the third, fourth, and fifth factors explained 10.213%, 8.861% and 6.956% of the total variance and called pH, Silica and nutrient factors, respectively. Multivariate statistical techniques can be effective methods to aid water resources managers understand complex nature of water quality issues and determine the priorities to sustain water quality.

Classification of Depressed Patients: A Cluster Analysis Derived Grouping

1971 ◽  
Vol 118 (544) ◽  
pp. 275-288 ◽  
Author(s):  
E. S. Paykel
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Depressed Patients

In recent years there has been a considerable interest in the classification of depressed patients, and in the use of multivariate statistical techniques as tools for classifying, with the hope of either validating traditional classifications or suggesting useful new ones. One technique employed for this purpose has been factor analysis. A number of studies have used this method to explore the overlapping endogenous-reactive or psychotic-neurotic dichotomies. Most have demonstrated a factor or factors reflecting such a dimension which appears to form a consistent, systematic source of variance in ratings of depressed patients (1, 5, 11, 15, 16, 18, 26, 31, 33).

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