scholarly journals Socioeconomic profile of producers and dairy technological of farms in the southern mesoregion of Santa Catarina

2022 ◽  
Vol 43 (1) ◽  
pp. 107-120
Author(s):  
Thalyta Marcílio ◽  
◽  
Bruno Alexandre Dombroski Casas ◽  
Diego Hemkemeier Silva ◽  
Vanessa Peripolli ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Social Economic ◽  
Sampling Error ◽  
The Other ◽  
Insufficient Data ◽  
Santa Catarina ◽  
Average Area ◽  
Socioeconomic Profile ◽  
Main Activity

This study characterized the socioeconomic profile of milk producers and dairy technological of farms in the southern mesoregion of Santa Catarina. Following a 6.5% sampling of total farms by municipality, 95% confidence level, 5% sampling error, and group heterogeneity, data were collected from 308 farms, 22 of which were excluded due to insufficient data. The farmers were selected randomly, and information extracted from an electronic form, addressing social, economic, technical and technological issues. The data were analyzed using factor, cluster, and discriminant analysis. As farms with the main activity of dairy farming, they have an average area of 20.79 hectares and a production of 12.18 liters per animal per day. I n the factor analysis, the first factor was related to the area and productivity of farms and the second factor to sanitary control and the feed variety of the animals. The cluster analysis formed three clusters; the first and the second were composed of larger farms and areas, and the other consisted of smaller farms, the latter involving more producers. As farms are characterized by low production, there is clearly a deficiency in technical support for producers.

Does Mutual Fund Management in India Correspond to its Investment Objective Classification?

2005 ◽  
Vol 08 (04) ◽  
pp. 659-685 ◽  
Author(s):  
Luis Ferruz Agudo ◽  
Cristina Ortiz Lázaro
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Mutual Fund ◽  
The Other ◽  
Fund Management ◽  
Institutional Control ◽  
Other Hand ◽  
Objective Classification ◽  
And Cluster Analysis

The aim of this article is to investigate the mutual fund market in India and verify whether or not the fund classification obtained from the name given to identify them corresponds to that which would be obtained were prior management to be taken into account. This industry has undergone spectacular growth in recent years, making this study extremely interesting, not least because institutional control could be less in times of expansion. The methodologies employed in the study are factor analysis and cluster analysis. The former determines that risk would clearly identify two groups of funds in the same manner as public classification of the funds. Cluster analysis, on the other hand, identifies funds that are, in fact, very close to one another, when for the bulk of investors they are not.

scholarly journals Study of Regional Disparities among Districts in East Java Province

2018 ◽  
Vol 3 (2) ◽  
pp. 95
Author(s):  
Enggar Dwi Novianto ◽  
Wiwandari Handayani
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Manufacturing Industry ◽  
Agricultural Sector ◽  
Regional Disparities ◽  
The Other ◽  
Factors Influencing ◽  
Other Hand ◽  
The People ◽  
And Cluster Analysis

Some evidences have emerged indicating that there are regional disparities in East Java Province and industrialization seems to give its contribution in creating regional disparities. In 2014, Manufacturing industry dominated the contribution to the GDP which was 29%, on the other hand mostly the people who worked in the agricultural sector, and so the land which mostly agricultural. This study aims to identify factors influencing the disparities in East Java Province. This statement is also strengthened by the Williamson index which showed that the regional disparities were quite high, with two districts indicated to contributing the most, Kediri and Surabaya City. By using factor analysis, this research will try to answer what factors influencing the disparities statistically, and cluster analysis is trying to figure out the disparities spatially. Then it is going to be proven that some districts agglomerated in a certain area and can implicate the disparities in East Java.

scholarly journals Construcción y validación de un instrumento diagnóstico para la representación cognitiva de la Orientación Psicopedagógica en Galicia

2014 ◽  
Vol 20 (2) ◽  
pp. 184
Author(s):  
José Antonio Sarmiento Campos ◽  
Camilo Isaac Ocampo Gómez ◽  
Alfonso Cid Sabucedo
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Theoretical Model ◽  
Structural Equations ◽  
The Other ◽  
Internal Reliability ◽  
Reliability Level ◽  
Technical Specifications ◽  
And Cluster Analysis ◽  
Degree Of Similarity

RESUMEN Se presenta el proceso de validación de un instrumento de diagnóstico compuesto por dos elementos: ontología de la orientación psicopedagógica y cuestionario para indagar sobre el modelo común de orientación entre los orientadores educativos de Galicia. En el artículo se muestran las especificacio‐ nes técnicas del cuestionario, cuyo índice de consistencia interna es de un Alpha de 0,947. Mediante análisis factorial, de conglomerados y ecuaciones estructurales se identifican dos modelos, uno teórico y otro empírico. La gran afinidad entre ambos da cuenta de la validez de constructo del instrumento. Las conclusiones y la prospectiva del trabajo constituyen la parte final del artículo. ABSTRACT The aim of this work claims the validation of an instrument of diagnosis composed by two elements: ontology of the psycho-pedagogical guidance and a questionnaire to investigate the existence of a common model of psycho-pedagogical guidancee among the educational counsellors of Galicia. The ontology has been elaborated on the basis of 22 bibliographical and 5 legislative sources, whereas the questionnaire has been validated with a sample of 105 educational counsellors of public centers of primary and secondary. Along the article there are studied the technical specifications of the questionnaire. The internal reliability level (Cronbach’s alpha) was 0,947. On the other hand, by means of factor analysis and cluster analysis, several factors are established, as well as its relations, which there form two models, the theoretical and different empirical one. Using structural equations there is veri‐ fied the adjustment of both models for, finally, to establish the degree of similarity (correlation) bet‐ ween them. The above mentioned contrast concludes in the great affinity between the theoretical model and the empirical model, which realizes of its high construct validity. Finally the conclusions appear, the prospective of the work and of the instrument used.

Analyses minéralogiques multivariées de sédiments du Wisconsinien supérieur au sud-ouest du Yukon

1996 ◽  
Vol 33 (1) ◽  
pp. 42-51 ◽  
Author(s):  
Véronique Dewez ◽  
Marie-Anne Geurts
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Flow Pattern ◽  
Relative Abundance ◽  
Heavy Mineral ◽  
The Other ◽  
Heavy Minerals ◽  
Sand Fraction ◽  
Ice Flow ◽  
Granitic Batholith

For this study, 84 samples of glacial and juxtaglacial sediments were collected in valleys of the Ruby Range and Aishihik Basin (southwestern Yukon). Analyses were conducted to quantify the heavy minerals in the sand fraction and to assess the petrography of the gravel fraction. A cluster analysis performed on the heavy mineral results showed five groups of deposits, three of which are related to local glaciers inside the Ruby Range, the other two being related to regional ice lobes of Kluane and Aishihik, respectively. The three groups of local sediments correspond to the three lithologies of the Ruby Range, i.e., the granitic batholith, the schists, and the alaskite. The sediments from the regional ice lobes are characterized by highly diversified mineralogy and petrography and the relative abundance of minerals from the Saint Elias Mountains, the main source of the ice lobes. A correspondance factor analysis performed on the heavy mineral results organizes samples and minerals into a triangular cloud, the three vertices corresponding to biotite, carbonate, and titanite–garnet. These are the key elements of local glaciers, Kluane ice lobe, and Aishihik ice lobe, respectively. Finally, the study shows the extension of Kluane lobe in one valley of the Ruby Range, the ice flow pattern in another valley, as well as a transfluence from Kluane lobe inside the Range.

Multivariate consumption profiling (MCP) for intelligent meter systems: a methodology to define categories and levels

2010 ◽  
Vol 10 (5) ◽  
pp. 710-720 ◽  
Author(s):  
J. L. Solanas ◽  
M. R. Cussó
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Multivariate Analysis ◽  
Discriminant Analysis ◽  
Reference Population ◽  
Statistical Analyses ◽  
Conceptual Schema ◽  
Data Variability ◽  
Water Companies ◽  
Analyse Data

Multivariate Consumption Profiling (MCP) is a methodology to analyse the readings made by Intelligent Meter (IM) systems. Even in advanced water companies with well supported IM, full statistical analyses are not performed, since no efficient methods are available to deal with all the data items. Multivariate Analysis has been proposed as a convenient way to synthesise all IM information. MCP uses Factor Analysis, Cluster Analysis and Discriminant Analysis to analyse data variability by categories and levels, in a cyclical improvement process. MCP obtains a conceptual schema of a reference population on a set of classifying tables, one for each category. These tables are quantitative concepts to evaluate consumption, meter sizing, leakage and undermetering for populations and groupings and individual cases. They give structuring items to enhance “traditional” statistics. All the relevant data from each new meter reading can be matched to the classifying tables. A set of indexes is computed and thresholds are used to select those cases with the desired profiles. The paper gives an example of a MCP conceptual schema for five categories, three variables, and five levels, and obtains its classifying tables. It shows the use of case profiles to implement actions in accordance with the operative objectives.

The five‐factor personality model in applied settings

1994 ◽  
Vol 8 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Itzhak Montag ◽  
Joseph Levin
Keyword(s):  
Factor Analysis ◽  
Personality Inventory ◽  
The Other ◽  
Factor Solution ◽  
Male And Female ◽  
Neo Personality Inventory ◽  
Clear Cut ◽  
Five Factors ◽  
Male Subjects ◽  
Female Subjects

Two studies of the Revised NEO‐Personality Inventory (NEO‐PI‐R) conducted on two different applicant samples (one consisting of 539 female subjects and the other consisting of 396 male subjects) are reported. Factor analysis of the female sample yielded a five‐factor solution, highly congruent with the factors presented by Costa, McCrae and Dye (1991). Results of the male data were less clear‐cut, yielding four to five factors which were moderately congruent with the American data. The combined male and female sample showed again high congruence coefficients. Various minor deviations in the location of the facet variables are discussed.

scholarly journals “Why (Should) I Do Something for the Environment?” Profiles of Flemish Adolescents’ Motivation Toward the Environment

2018 ◽  
Vol 10 (7) ◽  
pp. 2579 ◽  
Author(s):  
Wanda Sass ◽  
Jelle Pauw ◽  
Vincent Donche ◽  
Peter Petegem
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Secondary School ◽  
Secondary School Students ◽  
School Students ◽  
The North ◽  
Dutch Translation ◽  
Confirmatory Factor ◽  
Senior Secondary ◽  
Person Centered Approach

The Motivation Toward the Environment Scale (MTES), developed in Canada, measures people’s self-determined motivation for doing something for the environment. Answering the call by its original developers, this study further validated the MTES within a sample of 779 Dutch-speaking senior secondary school students, aged 17 to 19, in the north of Belgium. More specifically, reliability and construct validity of a Dutch translation of the MTES were verified. To this measure, confirmatory factor analysis was used, and the hypothesized simplex structure was tested through correlation analyses. Results confirmed the reliability of the MTES and a five-scale version of the MTES, excluding identified motivation, is introduced. This variable-centered approach was complemented by the adoption of a person-centered approach for identifying MTES profiles. Using cluster analysis, four meaningful MTES profiles emerged, with amotivation scoring medium to high in all but one. Theoretical implications of the findings and suggestions for interventions and further research are discussed.

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