In this paper ,the problem of point estimation for the two parameters of logistic distribution has been investigated using simulation technique. The rank sampling set estimator method which is one of the Non_Baysian procedure and Lindley approximation estimator method which is one of the Baysian method were used to estimate the parameters of logistic distribution. Comparing between these two mentioned methods by employing mean square error measure and mean absolute percentage error measure .At last simulation technique used to generate many number of samples sizes to compare between these methods.

     This paper discusses estimating the two scale parameters of Exponential-Rayleigh distribution for singly type one censored data which is one of the most important Rights censored data, using the maximum likelihood estimation method (MLEM) which is one of the most popular and widely used classic methods, based on an iterative procedure such as the Newton-Raphson to find estimated values for these two scale parameters by using real data for COVID-19 was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. The duration of the study was in the interval 4/5/2020 until 31/8/2020 equivalent to 120 days, where the number of patients who entered the (study) hospital with sample size is (n=785). The number o

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

     In this paper, a Monte Carlo Simulation technique is used to compare the performance of MLE and the standard Bayes estimators of the reliability function of the one parameter exponential distribution.Two types of loss functions are adopted, namely, squared error  loss function (SELF) and modified square error loss function (MSELF) with informative and non- informative prior. The criterion integrated mean square error (IMSE) is employed to assess the performance of such estimators .

The study involved the description of the environmental characters and distribution of Anogramma  leptophylla  (Annual  Maidenhair fern)  in Erbil and Garmian districts during May- 2017 in Kurdistan of Iraq. The geographical distribution of the taxa was recorded in Bani Bee region for the first time within the Garmian district but it was recorded before in the Zar Gali region within the Erbil district. The climatic characters of the studied site in Erbil district were: moist, cold and the elevation was up to 560 m above sea level with sandy clay soil texture whereas in the Garmian district: dry, hot, and the elevation was only 330 m  above sea level with sandy stone soil. Plant up to 13 cm long, megaphyl

The study area is located at AL Jabal AL-Akhdar region North Eastern part of Libya. The study includes (23) fresh samples that are taken from Darnah limestone Formation, these samples were distributed on and covered about (210) km2. The porosities and permeabilities of these samples were determined. This study is important because this formation is considered as a good reservoir for hydrocarbon accumulation in other places in Libya.
The porosity was measured by three different methods namely by porosimeter (using core samples), thin sections and binocular microscope. The permeability are also measured by two methods, the first method was by Nitrogen method and the other is by Klinkenberg method. The instrument that used for measuring