Obesity is a common disease that resulted from over-nutrition in adults and children. It rarely causes damage to the centers of food in the brain. Obesity is defined as an increased body weight from its natural limit which is resulted from the accumulation of excessive amounts of fatty tissue incredibly up to 20% in males, 30 % in females unless this increase is not due to an increase in muscles as in athletes or accumulation of water in the body which is resulted from Mesothelioma or the magnitude of the skeleton.Obesity is the increase of the total average of fat in the body compared to other tissues, which causes an increasing body weight, thereby increasing body mass. The fatty child has an increase in the stored fatty layer under the skin, and increased weight 20%more than the normal weight of other children in the same age and height.
This thesis focuses on identifying showing the relationship between obesity and some of the variables. Moreover, the thesis reflects the importance of maintaining the ideal weight of the child and his role in the growth and health. The evidence shows that children who suffer from obesity are more likely to become fat adults, so they are exposed to increased risk of serious health problems. Hence, protecting children from obesity and treating them is possible through changing lifestyle, improving the child's nutrition system, and urging him to exercise to improve their health at the present time and in the future.
Therefore, the thesis aims: to detect significant differences in obesity for kindergarten children depending on certain variables through the testing hypothesis as followed: Statistically there are no significant differences in obesity with kindergarten children that are attributable to the following variables:
(A)Sex variable.
(B) The sequence of the child in the family..
(C) Dietary habits of the family.
To achieve the objectives of this study, 300 children were selected as samples, 166 males and 134 females. One of the most important tools that were used is:
1 - an electronic device for measuring weight.
2 - Length measuring tape.
3 - Measurement of body mass index (BMI)..
The researcher used in data statistical analysis:
(1) One way Anova.
(2) The T- test for two independent samples: Independent Samples Test.
(3) The real bilateral correlation coefficient (Point Bay Cyril).
The most important results that have been reached:
(1) That females suffer from obesity more than males because the body mass index of females is greater than the body mass index (BMI) for males.
(2) There is no statistically significant difference between the averages of body mass index (BMI) scores for kindergarten children due to the variable of the sequence of the child within his brothers.
(3) There is no statistically significant difference between the averages of body mass index (BMI) scores for obese kindergarten children that is attributed to behavioral tendencies variable of the child.
Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.
The interest of this paper is that
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PVA:PEG/MnCl2 composites have been prepared by adding (MnCl2) to the mixture of the poly vinyl alcohol (PVA) and poly ethylene glycol (PEG) with different weight percentages (0, 2, 4, 6, 8 and 10) wt.% by using casting method. The type of charge carriers, concentration (nH) and Hall mobility (μH) have been estimated from Hall measurements and show that the films of all concentration have a negative Hall coefficient. In D.C measurement increase temperature leads to decrease the electrical resistance. The D.C conductivity of the composites increases with the increasing of the concentration of additive particles and temperature. The activation energy decreases for all composites with increasing the concentration of the additive particles.
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