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    EXPLORATORY DATA ANALYSIS AND MULTIVARIATE STRATEGIES FOR REVEALING MULTIVARIATE STRUCTURES IN CLIMATE DATA

  • subjectCategory: Physical Sciences
  • access_time18 December, 2016
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    This paper is on data analysis strategy in a complex, multidimensional, and dynamic domain. The focus is on the use of data mining techniques to explore the importance of multivariate structures; using climate variables which influences climate change. Techniques involved in data mining exercise vary according to the data structures. The multivariate analysis strategy considered here involved choosing an appropriate tool to analyze a process. Factor analysis is introduced into data mining technique in order to reveal the influencing impacts of factors involved as well as solving for multicolinearity effect among the variables.  The temporal nature and multidimensionality of the target variables is revealed in the model using multidimensional regression estimates. The strategy of integrating the method of several statistical techniques, using climate variables in Nigeria was employed. R2 of 0.518 was obtained from the ordinary least square regression analysis carried out and the test was not significant at 5% level of significance. However, factor analysis regression strategy gave a good fit with R2 of 0.811 and the test was significant at 5% level of significance. Based on this study, model building should go beyond the usual confirmatory data analysis (CDA), rather it should be complemented with exploratory data analysis (EDA) in order to achieve a desired result.

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    ON THE ANALYSIS OF STROKE IN INFANT IN ENUGU STATE: A POISSON PROCESS.

  • subjectCategory: Physical Sciences
  • access_time18 December, 2016
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    The incidence of stroke is usually associated with adults and the elderly. Little or no knowledge of the incidence is associated with infants, children, and young adults; as such cannot even be thought to occur before birth. In media enlightenment on the existence of stroke in infants which took place in Enugu State; many were unaware of the incidence of stroke in infants in that region.  Therefore this study aimed at verifying the existence of the incidence of stroke in infants in Enugu State. Recorded data confirmed the existence of this illness in infants; although it is seen as a rear occurrence. The existing data were analysed using the Poisson distribution function to determine if the data followed a random process. The result of the analysis led to the acceptance of the fit at 5% significance level; this revealed that the data used for the study followed a random process. However it is pertinent to mention that this illness is actionable. This study therefore calls for more awareness on the existence of this illness in infants to forestall future/further occurrences.

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