Statistical Analysis of Impact of Stock Market Performance on the Growth of Nigerian Economy
Stock market is a mechanism through which the transaction of financial assets with life span of greater than one year takes place. Financial assets may take different forms ranging from the long-term government bonds to ordinary shares of various companies. This study was carried out to examine the role which the stock market plays in the growth process of the Nigerian economy. The Co-efficient of Determination (R2) was used to measure the goodness of fit of the model. The F-statistics was used to test the overall significance of a model. The Student t-test was used to determine the statistical significance of parameter estimates. Jacque-Bera Residual Normality Test was conducted to assert if the error term follows a normal distribution. The result of the t-test revealed that the coefficient for market capitalization, investment rate and real exchange rate are all statistical significant at 5 percent level of significance. But the coefficients of real interest rate were not statistically significant at 5 percent level of significance. The R2 which is the coefficient of multiple determinations also revealed that 99 percent of the variation in the dependent variable is caused by the variation in the explanatory variables. The F test result showed that the model is fit.
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On Bayesian estimator from exponential distribution based on records with presence of outliers
In this paper, Bayes estimator is derived for the parameter of the exponential model with presence of outliers based on records value. This estimator compared with estimator when we not use of records value.
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The analysis of stress around tunnel in shear stress domain
One of the important models in tunnel design and underground structures are determining the stresses and stress concentrations around them. The method of analysis is usually based the theory of elasticity. Therefore; it has the advantages of accuracy and uniqueness respect to the numerical models. The stress conditions in subsurface or underground domains are usually in the form of both normal and shear stresses. Those are because of the geological features such as bedding, jointing, folding and nonuniformity of petrology. Therefore; the directions of principal stresses are not parallel to the original Cartesian coordinates and they make specific angles to the x and y-axis. The analysis is two-dimensional for circular tunnel and it is applied for plane stress and plane strain conditions. The analysis can be applied for the case of supporting pressure pi. The radial and tangential deformations could also be determined at the roof and walls of tunnel.
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Multivariate dual to ratio type estimators using arithmetic, geometric and harmonic means in simple random sampling
Auxiliary variable is extensively used in survey sampling to improve the precision of estimates. Whenever there is availability of auxiliary information, we want to utilize it in the method of estimation to obtain the most efficient estimator. In this paper using multi-auxiliary information we have proposed estimators based on arithmetic, geometric and harmonic mean. It was also shown that estimator based on harmonic and geometric means are more biased than estimator based on arithmetic mean under certain conditions. However, the MSE of all three estimators are same up to the first order of approximation.
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State-dependent model for the analysis of inflationary rates
In this study, an extension of the class of state-dependent model (SDM) for which optimal forecasts may be computed using a recursive examination procedure referred to as the Kalman filter is developed for the analysis of Inflationary rates in Nigeria. The SDM formulation yields a practical means of estimation for the complex time varying dynamical process and provided a generic flexible framework for inflationary rate modelling and inference. A straight forward implementation was achieved in the study by the use of R software package.
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Different applied statistical methods to evaluate the response of cotton production to climatic variables
This study investigates the predicted effects of climatic factors during convenient intervals (in days) on cotton flower and boll production compared with daily observations. Also, covers the statistical relationship between climatic variables and aspects of cotton production and the effects of climatic factors prevailing prior to flowering or subsequent to boll setting on flower and boll production and retention in cotton. Further, cotton flower and boll production as affected by climatic factors and soil moisture status has been considered. Evaporation, sunshine duration, relative humidity, surface soil temperature at 1800 h, and maximum air temperature, are the important climatic factors that significantly affect flower and boll production. The least important variables were found to be surface soil temperature at 0600 h and minimum temperature. The five-day interval was found to be more adequately and sensibly related to yield parameters. Evaporation; minimum humidity and sunshine duration were the most effective climatic factors during preceding and succeeding periods on boll production and retention. There was a negative correlation between flower and boll production and either evaporation or sunshine duration, while that correlation with minimum relative humidity was positive. The soil moisture status showed low and insignificant correlation with flower and boll production. Higher minimum relative humidity, short period of sunshine duration, and low temperatures enhanced flower and boll formation.
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Model – Assisted Estimation in Adaptive Sampling
Two problems often crop up in adaptive sampling. One, it may not be feasible to sample according to a designated sampling plan. And two, the prescribed sampling plan may result in very small selection probabilities for some units thereby giving large weights to such units in estimation. In order to ameliorate these problems, a regression procedure that combines design and model-based techniques of estimation is proposed. Adaptive sampling designs are designs in which additional units or sites for observation are selected depending on the interpretation of observations made during initial sampling. Additional sampling is driven by the observed results from an initial sample. The results from this study demonstrate that the existing Horvitz-Thompson estimator for adaptive cluster sampling can be improved using model assistance.
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Signal model for the prediction of wind speed in Nigeria
Rapid development of wind energy as an alternative source of power is providing rich environment for wind energy related research. Several mathematical models have been used to study wind data and the models are mainly physical and statistical models. In this study, a signal Modeling approach is developed to predict wind speed data in Nigeria. The signal modeling approach is based on the Markov property, which implies that given the present wind speed state, the future of the system is independent of its past. A Markov process is in a sense the probabilistic analog of causality and can be specified by defining the conditional distribution of the random process.
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A Family of Estimators for Population Variance Using Two Auxiliary Variables
This paper deals with the problem of estimating the population variance when some information on two auxiliary variables is available. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The study is also extended to two-phase sampling. Theoretical results are supported by an empirical study.
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Treatment seeking behaviour of infertility in Uttar Pradesh: A comparison of rural and urban females
Infertility is considered as critical health problem among all societies all over the world. Infertility has many consequences for men and especially for women. Couples experience stigma, sense of loss, and diminished self-esteem in the setting of their infertility. Childless couples are stigmatized and discriminated against society. The blame for infertility is unquestioningly placed on the women. In this study an attempt has been made to estimate infertility. In this study an attempt has been made to estimate infertility from the direct questions regarding infertility and health seeking behaviour in Uttar Pradesh using the DLHS-III survey data collected in 2007-08. Here the study has been done for rural and urban regions separately. Chi-square techniques have been used to dependency of infertility on the various socio-demographic characteristics. Prevalence of lifetime infertility as well as lifetime primary infertility is higher in rural than urban areas. Treatment seeking is slightly higher among urban than rural women but there is not very big difference. Infertility is perceived as a problem across virtually all cultures and societies. The number of couples seeking treatment for infertility is increasing now-a-days due to more awareness of available services and latest and more successful techniques.
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