Prevalence of Anxiety Disorder using Zung Scale

This study was presented to Illustrate the concept in a comprehensive manner and symptoms of anxiety disorder and what are the factors that lead to anxiety disorders in adults. Sample was taken from a group of staff and both sexes working in three hospitals in the province of  Babylon and test the data using T- Test depend on Zung  measure. Keywords: T- test , Anxiety disorder, Test Zung  Anxiety , Zung Scale For   Anxiety

On Randomized Complete Block Design

This study presented the  evaluate of 20 types of cancer disease in Tikrit teaching hospital in Tikrit for the period from 1995 to 2005 . the data analyzed by RCBD (Randomized complete block design) to explain the significant difference between all kind of cancer disease and all age groups

On Student Comprehension For There Year Courses In Mathematics Department

In this paper, we present the significant difference between the level of student comprehension for these year courses and for all student of mathematical department,college of science, Kufa university .Moreover to find out the effect of scientific, personality,ability of evaluation and ability of communication To have the goal ,we used some statistical methods like experimental design,correlation and regression analysis

On the estimation of survival function and parameter exponential life time distribution.

The study and research of survival or reliability or life time belong to the same area of study but they may belong to a different area of application. In survival analysis one can use several life time distribution, exponential distribution with mean life time q is one of them. To estimate this parameter and survival function we must be used estimation procedures with less MSE and MPE. Approach: The only statistical theory that combined modeling inherent uncertainty and statistical uncertainty is Bayesian statistics. The theorem of Bayes provided a solution to how learn from data. Bayes theorem was depending on prior and posterior distribution and standard Bayes estimator depends on Jeffery prior information. In this study we annexed Jeffery prior information to get the modify Bayes estimator and then compared it with standard Bayes estimator and maximum likelihood estimator to find the best (less MSE and MPE). Results: when we derived Bayesian and Maximum likelihood of the scale parameter and survival functions. Simulation study was used to compare between estimators and Mean Square Error (MSE) and Mean Percentage Error (MPE) of estimators are computed. Conclusion: The new proposed estimator of modify Bayes estimator in parameter and survival function was the best estimator (less MSE and MPE) when we compared it with standard Bayes and maximum likelihood estimator

On Student Comprehension For There Year Courses In Mathematics Department

In this paper, we present the significant difference between the level of student comprehension for these year courses and for all student of mathematical department,college of science, Kufa university .Moreover to find out the effect of scientific, personality,ability of evaluation and ability of communication To have the goal ,we used some statistical methods like experimental design,correlation and regression analysis

Comparison of the Bayesian and maximum likelilhood estimation for Weibull distribution

Problem statement: The Weibull distribution has been widely used especially in the modeling of lifetime event data. It provides a statistical model which has a wide variety of applications in many areas, and the main advantage is its ability in the context of lifetime event, to provide reasonably accurate failure analysis and failure for ecasts especially with extremely small samples. The conventional maximum likelihood method is the usual way to estimate the parameters of a distribution. Bayesian approach has received much attention and in contention with other estimation methods. In this study we explore and compare the performance of the maximum likelihood estimate with the Bayesian estimate for the Weibull distribution. Approach: The maximum likelihood estimation, Bayesian using Jeffrey prior and the extension of Jeffrey prior information for estimating the parameters of Weibull distribution of life time are presented. We explore the performance of these estimators numerically under varyin g conditions. Through the simulation study comparison are made on the performance of these estimators with respect to the Mean Square Error (MSE) and Mean Percentage Error(MPE). Results: For all the varying sample size, several specific values of the scale parameter of the Weibull distribution and for the values specify for the extension of Jeffrey prior, the estimators of the maximum likelihood method result in smaller MSE and MPE compared to Bayesian in majority of the cases. Nevertheless in all cases for both methods the MSE and MPE decrease as sample size increases. Conclusion: Based on the results of this simulation study the Bayesian approach used in the estimating of Weibull parameters is found to be not superior compared to the conventional maximum likelihood method with respect to MSE and MPE values

Statistical Analysis on Student in Department of Mathematics (2007-2008)

This paper introduce statistical analysis on sample of mathematical student in college of science , Kufa university .A questionnaire was answered by all student in mathematics department . The aim was to investigate the desire of students to be mathematics teacher, go for higher study in one hand , and student opinions of their teachers from four variable namely , personality , scientific knowledge,ability of communication with students,the ability of evaluation ,using Excel program to draw graphs ,and factorial experiments to analyze data

Statistical Analysis on Student in Department of Mathematics (2007-2008)

This paper introduce statistical analysis on sample of mathematical student in college of science , Kufa university .A questionnaire was answered by all student in mathematics department . The aim was to investigate the desire of students to be mathematics teacher, go for higher study in one hand , and student opinions of their teachers from four variable namely , personality , scientific knowledge,ability of communication with students,the ability of evaluation ,using Excel program to draw graphs ,and factorial experiments to analyze data

Bayes estimator for exponential distribution with extension of Jeffery prior information

In this paper the extension of Jeffery prior information with new loss function for estimating the parameter of exponential distribution of life time is presented. Through simulation study the performance of this estimator was co mpared to the standard Bayes with Jeffery prior information with respect to the mean square error(MSE)and mean percentage error (MPE). We found the extension of Jeffery prior information gives the best estimator