This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

The media, especially the satellite channels in our time, are one of the most important pillars of daily life, public and private, for society and people, and are considered by sociologists and sociologists as one of the most important factors of social upbringing and the most important, as a result of the technological and technological development of the media as well as increasing their numbers and vertical and horizontal expansion locally, As well as entering into the lives of individuals and people and leading them to important sites within their interests and preferences, not to mention the long time spent exposure to those media and benefit from the programs offered or broadcast. , The problem of this research is that there is a l

There is no doubt that the field of education and teaching (in any country and whatever its ruling system varies “d”) is considered one of the most specific and sensitive field, because it is related to the building of human. And as the human is a purpose (aim) and the means in the same time and he is the strategist capital, so he way of his rearing, education, choosing the educator, methods of working and the aims are considered serious matters.

     The educational process has aim determined by the society for him self through its working establishments in this field and these are the official and public establishments. And as he feels that the establishments have failed to achieve its d

Electricity consumption for household purposes in urban areas widely affects the general urban consumption compared to other commercial and industrial uses, as household electricity consumption is affected by many factors related to the physical aspects of the residential area such as temperature, housing unit area, and coverage ratio, as well as social and economic factors such as family size and income, to reach the extent of the influence of each of the above factors on the amount of electricity consumed for residential uses, a selected sample of a residential area in the city of Baghdad was studied and a field survey conducted of the characteristics of that sample and the results analyzed and modeled statistically in relation to the amo

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a