Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

Often times, especially in practical applications, it is difficult to obtain data that is not tainted by a problem that may be related to the inconsistency of the variance of error or any other problem that impedes the use of the usual methods represented by the method of the ordinary least squares (OLS), To find the capabilities of the features of the multiple linear models, This is why many statisticians resort to the use of estimates by immune methods Especially with the presence of outliers, as well as the problem of error Variance instability, Two methods of horsepower were adopted, they are the robust weighted least square(RWLS)& the two-step robust weighted least square method(TSRWLS), and their performance was verifie

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First: the problem of research and its importance

      The teacher's success in facilitating the students' learning and growth according to the educational and educational goals set out, he must identify the problems of discipline of students in the classroom in terms of sources and reasons and types and methods of prevention and treatment and the teacher to remember that success in his teaching and instruction is not completed more fully once he has the information And knowledge of the subject of the lesson, but must understand the dynamics of the group (class group) and master the skills of classroom management, su

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The prophet said that it anybody burdened any of the people or the book more than they could endure he would ben his opponent until the day of judgment.

-under the rightly guided caliphs the Christians had much freedom .this is shown by a letter attributed to ishu-yab III. The Nestorian catholics.

-The third caliph,Uthman favoured the Christians either because of the spcial skills or abilities which they possessed or through the imfluence of his Christian wife Na'ila.

-Under the early Umayyade,the christiansins the Isalamic umma had as much freedom as they had previously enjoyed under the best of their Christians governments because they restorted their churches and appointed many Christians to the

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

The current research involves psychological pressure (educational,environment andemotionly) for secondary level to 2013-2014.This research includes comparison among students who are trained and not trained  in physical education .The sample is(126) students from each gender from first education.Al-Karkh and the research found out that physical education  has an effect in lessing emotional and educational in a big degree in student in secondary  which affect them  positively in their  study.                                     &n