Analysis of JAMB Examination Results: Using Cluster and Canonical Correlation Techniques.

This study investigates JAMB examination results for 2006. The data consist of scores of 225 students. Out of twenty-three subject areas which the students sat for, eleven subjects were used for the study. The data was subjected to cluster and canonical correlation analysis .The essence was to divide the subjects into smaller number of classes such that objects in the same class are similar to one another. The complete linkage method of cluster analysis was employed to this effect, while canonical correlation analysis was employed to investigate the relationship between these groups.  The results show that two groups were formed. Group A consists of Government, religion, mathematics, commerce, and literature-in-English, while Group B consists of   English, biology, chemistry, agriculture, economics, and physics. Five canonical roots were obtained and only one is statistically significant. However, group A is inversely related to group B indicating results from mathematics, commerce and religion show the strongest relationship and weighted heaviest among the subjects. While Chemistry, Economics and Agriculture appeared to be low with weak relationship and weighted lighter among the subjects. Keywords canonical correlation, cluster analysi

USO DE ANÃLISE ESTATÃSTICA MULTIVARIADA PARA TIPIFICAÇÃO DE PRODUTORES DE LEITE DE MINAS GERAIS

The present work had as its main objective to identify and characterize milk production systems through methods of multivaried statistical analysis. Factorial analysis, cluster, discriminant and canonical correlation were utilized. The production gradation and defrayal were the main classification criterium among the productors. Combining the results obtained with the cluster analysis and the canonical correlation analysis, the second classification analysis aggregates the grazing lands and the care with the flock health. Three productors groups were identified, among which the first one is prominent for aggregating about 90% of the total analyzed and is composed by relatively smaller productors. The discriminant analysis and the measuring among financial indicators confirm such classification.multivaried analysis, milk cattle raising, Minas Gerais., Livestock Production/Industries, Research Methods/ Statistical Methods,

Image patch analysis and clustering of sunspots: a dimensionality reduction approach

Sunspots, as seen in white light or continuum images, are associated with regions of high magnetic activity on the Sun, visible on magnetogram images. Their complexity is correlated with explosive solar activity and so classifying these active regions is useful for predicting future solar activity. Current classification of sunspot groups is visually based and suffers from bias. Supervised learning methods can reduce human bias but fail to optimally capitalize on the information present in sunspot images. This paper uses two image modalities (continuum and magnetogram) to characterize the spatial and modal interactions of sunspot and magnetic active region images and presents a new approach to cluster the images. Specifically, in the framework of image patch analysis, we estimate the number of intrinsic parameters required to describe the spatial and modal dependencies, the correlation between the two modalities and the corresponding spatial patterns, and examine the phenomena at different scales within the images. To do this, we use linear and nonlinear intrinsic dimension estimators, canonical correlation analysis, and multiresolution analysis of intrinsic dimension.Comment: 5 pages, 7 figures, accepted to ICIP 201

Statistics for evidence-based policy in the Church of England : predicting diocesan performance

This study computed the percentage changes recorded on six separate performance indicators between 1991 and 2000 in order to calculate the effect of the Decade of Evangelism on the mainland dioceses of the Church of England. The performance indicators were usual Sunday attendance, Easter Sunday communicants, Christmas communicants, electoral roll membership, total baptism figures, and total confirmation figures. Statistical procedures (including cluster analysis, analysis of variance, canonical correlation analysis, and multiple regression) were then employed in order to identify from the range of variables routinely collected by the central church authorities policy-related factors associated with church growth (or at least reduced decline) over this period. These analyses identified four areas, concerned with expanding non-stipendiary ministry, with encouraging the ordination of women, with resisting church closure, and with promoting a financial policy that includes planned subscriptions and charitable giving. These conclusions are offered as an applied example of using statistics as a tool for mission and as the basis for evidence-based policy

The role of personal information sources on the decision-making process of Costa Rican dairy farmers

The attitudes of farmers in relation to the importance of different people as information and opinion sources (InfS) for different phases of the decision-making process were studied in 91 Costa Rican dairy farmers. The InfS studied were: Family members, Other farmers, Technical advisors, Farm staff and Commercial agents, while the phases were: Problem detection, Seeking for problem solutions, Seeking for new practices and Seeking for opinion. A Multidimensional Preference Analysis (MDPREF) was used to obtain a two-dimensional map of preference of the farmers. A factor analysis was used to define new variables representing the farmers' predilection towards the InfS. A canonical correlation analysis was performed to find-out simple and canonical correlation between farmers'/farms' characteristics and the InfS preferences. Informational profiles in the population were defined through a Cluster Analysis. The MDPREF suggests that Family members and Technical advisors were the most preferred InfS. However their relative importance changed throughout the phases. Farm staff were rated in third place and their role became more important in the ‘Problem detection’ phase. Other farmers and Commercial agents were, in general, the less preferred information sources. The former became slightly more important in the ‘Seeking for new practices’ phase. The canonical correlation analysis found three low-medium correlations between the farmers'/farms' characteristics and the InfS factors. These correlations showed that the farmers' age, educational level and dedication and the farms' characteristics of area, herd size and distance to population centres had significant influence on the preference of the farmers towards different information sources. The cluster analysis found nine groups of similar farmers according to their preferences towards informational sources. Some implications mainly for extension activities are also stated and discussed. The importance of different informational sources slightly change throughout the decision-making steps, the family and farm staff being the most preferred information sources

Forecasting Season Onsets in Kapuas District Based on Global Climate Model Outputs

Predictions of the rainy and dry season onsets are very important in climate risk management processes, especially for the development of early warning system of land and forest fires in Kalimantan. This research aims to predict the rainy and dry season onsets in two cluster regions in Kapuas District, Central Kalimantan. The prediction models used to predict the onsets are developed by using seasonal rainfall data on September-October-November (SON) periods as predicted by five Global Climate Models (GCMs). The model uses Canonical Correlation Analysis (CCA) method available in the Climate Predictability Tool (CPT) software developed by the International Research Institute for Climate and Society (IRI), Columbia University. The results show that the predictors from HMC and POAMA models produce better canonical correlations (r = 0.72 and 0.89, respectively) compared to BCC (r=0.46), CWB (r=0.62), and GDAPS_F (r=0.67) models. In the development of models for predicting the dry season onsets, the predictors from CWB and POAMA models perform better canonical correlation results (r = 0.73 and 0.76, respectively) compared to BCC (r=0.53), GDAPS_F (r=0.64), and HMC (r=0.46) models. In general, the model validations showed that CWB, GDAPS_F, and POAMA models have better predictive skills than BCC and HMC models in predicting onsets of the rainy and dry seasons (with Pearson correlations (r) ranging between 0.30 and 0.75). Experiments on those five models for the predictions of rainy season onset in 2013 showed that the predicted onsets occurred on the range of 8 September to 22 October in Cluster 1 and on 3 to 7 October in Cluster 2. For the predictions of the dry season onsets in 2014, the models predicted the occurrences from 6 to 25 May in Cluster 1 and from 21 to 25 March in Cluster 2

THE TRUST IN INSTITUTIONS AND MANAGER ASSOCIATION

Recent research suggests that greater business co-operation between enterprises is associated with a higher level of social capital of an individual. Since managers are basically people who base their activity on co-operation, the goal of this paper is to establish a link between the level of social capital of managers in cluster-based companies with their assessment of the activity and results of those activities in clusters. The analysis includes all dimensions and elements of social capital and the perception of managers on the business results of mutual cooperation. For this purpose, the Canonical correlation analysis (CCA) and the nonparametric statistical method (Kendall Tau-b correlation; τb) were used to avoid the conclusion using only one of the methods. The results have shown that there is a statistically significant, but weak, correlation between trust in institutions and active membership in associations with managers\u27 assessment of joint activities within the cluster. This research has shown that there is a statistically significant association between multiple memberships of managers in associations with their higher grade of activity within the cluster. The results have shown that general trust and perception of compliance with the norms of citizens is negatively associated with a higher grade of cluster activity, but these results are not statistically significant

APLIKASI ANALISIS KORELASI KANONIK UNTUK MELIHAT HUBUNGAN ANTARA DIMENSI DARI VARIABEL MOTIVASI DENGAN DIMENSI DARI VARIABEL KINERJA

Analisis korelasi kanonik (canonical analysis) pertama kali diperkenalkan oleh Hotelling (1936), sebagai suatu teknik statistika peubah ganda (multivariat) yang menyelidiki keeratan hubungan antara dua gugus variabel. Gugus yang dimaksud adalah kelompok. Satu gugus variabel diidentifikasikan sebagai gugus variabel penduga (independent variables), sedangkan gugus variabel lainnya diperlakukan sebagai gugus respon (dependent variables). Penelitian ini bertujuan untuk mengetahui hubungan dari dimensi dari variabel independen yaitu Variabel Motivasi dengan dimensi dari variabel dependen yaitu Variabel Kinerja, dan mengetahui bentuk fungsi kanonik dari aplikasi analisis korelasi kanonik terhadap pengaruh hubungan antara dimensi dari variabel motivasi dengan dimensi dari variabel kinerja. Hasil dalam penulisan skripsi ini berupa besaran nilai korelasi setiap variabel motivasi dengan variabel kinerja berikut dengan nilai determinasinya, dan fungsi kanonik yang didapatkan dengan menggunakan software SPSS ver. 23.0. ..... Canonical correlation analysis was first introduction by Hotelling (1936), as a statistical technique double variabels (multivariate) who insvestigates the close relationship between two a cluster of variables. A cluster of was defined as a group. A cluster of one variable identified as a cluster of independent variable, while a cluster of other variables treated as a cluster of dependent variables. This research aims to understand the relation of the dimensions of the independent variable, namely motivation variable with the dimensions of the dependent variable, namely performance variable, and to know the function form of application canonical correlation analysis against the influence of the relation between dimensions of motivation variable with performance variable. The results in this thesis will be to provide the amount of the correlation value each variable motivation with a variable performance following by determination value, and function canonical obtained by the use of software SPSS ver. 23.