Research aims to know the impact beyond the defined in the collection. The research community is the second school students at Baghdad University and a research sample (63) students, the number of experimental group (27) students and a control group (30) students. The researcher was rewarded in variable lifetime for students and educational attainment and educational level of the parents and the educational level of mothers. The researcher has developed a test took the number of paragraphs (20). A test was true after it has been submitted to the Group of arbitrators. The test was consistent with test method used and the reliability coefficient (0, 88). Either the statistical methods used by the researcher are: Pearson correlation coefficient of t-test and cronbach alpha. The researcher found the following results:
The concept of fully pseudo stable Banach Algebra-module (Banach A-module) which is the generalization of fully stable Banach A-module has been introduced. In this paper we study some properties of fully stable Banach A-module and another characterization of fully pseudo stable Banach A-module has been given.
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used
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The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for
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