A Statistical Analysis Method For The Number Of Mental States

The mental state can reflect the operation and technical level of the actual workers as required.When we evaluate one's work,the deviation between the result and the required standard is considered as the judgment.The result will be judged as unqualified,if the deviation comes to be too large or exceeds a certain value.As the deviation naturally obey normal distribution,for the demand,namely some kind of mental state,deviation distribution tends to be what workers need but no longer the normal distribution.So the distribution is more valuable than the normal distribution in the working environment.Firstly,this paper expounds the background and development of the mental state and the skewness distribution.Reference to previous researches,the distribution properties and numerical characteristics of the two parameter normal distribution are obtained.According to its properties,several methods of moment estimation and maximum likelihood estimation are used to estimate the parameters,and some Bayes estimation methods are presented.All the methods are compared by Monte Carlo simulation.Therefore,it can be concluded that the two kinds of moment estimation methods I present have better effect in different situations.Then the interval estimation of the parameters is given,and the influence of the chi square distribution and the central limit theorem on the interval length is discussed under different environmental conditions.Secondly,the statistical analysis method of the three parameter normal distribution presented gives the results and comparison of the moment estimation and maximum likelihood estimation.We can see,maximum likelihood estimation is better while the number of the samples is large.Considering that the variance of positive and negative deviation of two parameter normal distribution is not equal,I present the parameter 0,which is the ratio of positive and negative deviation of the standard deviation.Three parameter generalized skewness distribution is presented.Moment estimation and maximum likelihood estimation are used to estimate the parameters.With control variables in the Monte Carlo simulation,the maximum likelihood estimation has the better fitting effect of c,while the moment estimation has the better fitting effect of ?.Further,it's about the statistical analysis method of four parameter generalized skewness distribution with the new position parameter.In the simulation of Monte Carlo,the parameters are estimated by the maximum likelihood estimation.Then two parameter normal distribution statistical analysis method,which is different from the three parameter generalized normal distribution,has positive deviation and negative deviation variance value instead of the mental state c.Compared with the existing research methods in the literature in the simulation of Monte Carlo,my moment estimation has a better fitting effect.On the basis of above,I present the statistical analysis method of three parameter skewness distribution with the new position parameter.Moment estimation and maximum likelihood method are used to estimate the parameters.However,the solving process is too complex to obtain the simulation results.Finally,the methods are demonstrated through an example.