In recent years, the attention of researchers, governments and international non-governmental organizations has focused on the aggressive practices adopted by companies with the aim of evading the tax burden or from paying the tax obligations imposed on them by law, as the results of these practices are negatively affected by tax revenues. And that companies are part of the society in which they work, and they have rights and obligations, including paying taxes. The research community is the Iraqi private shareholding companies, and the research sample was 4 companies within the private sector and in the field and finance - banking, insurance, industrial and service, which are Ashur Bank, Al-Ahlia Insurance Company, Baghdad Soft

In recent years, the attention of researchers, governments and international non-governmental organizations has focused on the aggressive practices adopted by companies with the aim of evading the tax burden or from paying the tax obligations imposed on them by law, as the results of these practices are negatively affected by tax revenues. And that companies are part of the society in which they work, and they have rights and obligations, including paying taxes. The research community is the Iraqi private shareholding companies, and the research sample was 4 companies within the private sector and in the field and finance - banking, insurance, industrial and service, which are Ashur Bank, Al-Ahlia Insurance Company, Baghdad Soft

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

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