Objective(s): current study aims to find the effect of electronic games on children's behavior, and find the
relationship between child demographic data and the effect of electronic games on the child's behavior.
Methodology: A descriptive-analytic study was conducted for assessing the Effect of electronic games on
children's behaviors that attending to teaching hospitals in Baghdad city during the period of (October/ 20th
/2017 to March/1st /2018). A (50) purposive (non- probabilistic) sample from: Child Protection teaching
Hospital, Child Central Hospital in AL-Iskan. The sample is selected according to the criteria: Children who
visited the consulting unit of children in the hospitals in the first visit, children in the age between 7 and 12
years, boys and girls and their parents must be founded with them to help in the fill of the questionnaire. The
data are collected for the present study through the use of the questionnaires and semi-structured interview
technique. The data have been analyzed by using the descriptive statistics (Frequencies, Percentages, Means
and Standard Deviations (SD) and the inferential statistics (Chi-square to find out the relationships between the
socio-demographic and the effect of electronic games on the child's behavior).
Results: study results show that 70% of study sample was boys and 45% of them was between 9-10 years and
100% from the study sample have electronic game devices and 72% of them was playing every day, 24% play
for one hour or three hours. And that 52% of study sample have problems with the study, and their significant
statistical association in (p-value=0.026) between gender and behavioral problems of children.
Recommendations: study recommended for the importance of awareness of parents and educators to the right
way for using electronic games and supervise and guide theme to reduce the its negative effect on children
The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <
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