Global Structural Changes and Global Islamic Identity

Globalization is slowly changing life and traditions of many people over the World, dramatically seeking changes in the traditional relationship between the community and people, creating a new sensibility and creativity in relationships between social groups. These changes necessarily require a new social and political model of organization for community, reorganizing and changing the nature of relationship between states.  Effort to protect identity of people usually convey in the form of the fear of the subservient economic, cultural and political position in the process of globalization. This fear frequently produces powerful vibrations indicating the need of integration of social groups with the same or similar cultural identity, what opens up a new dimension of the internal political crisis between government and society. This crisis will produce particularly dramatic changes in Islamic world generating a powerful conflict between state and society in Islamic world, with unpredictable development of relations between Islam and West.

Recent Advances in Detecting Outliers in Moment Distributions

The study of outliers is one of the challenges existed for at least several hundred years. Outliers are the observations which are stranger from the bulk of data. Sometimes outliers may not be noticed but most of the times they can change the entire statistical data analysis. At the earlier stage of the data analysis, summary statistics such as the sample mean and variance, outliers can cause totally different conclusion, e.g. a hypothesis may or may not be rejected due to outliers. In fitting regression line outliers can significantly change the slope and 2R . If the detection of outliers is not done properly before data analysis then it may lead to model misspecification, biased parameter estimation and incorrect results. It is therefore pertinent to identify the outliers prior to proceed further for analysis and modeling. Much work has been done in Univariate probability distributions. The objective of this study is to develop the methods which are used to detect the outliers in Univarite Moment Distributions. Two discordancy tests are developed to detect the single and two outliers from data characterized by Moment distributions. The exact distribution of developed tests does not exist, therefore for finding the Tables of critical values simulation study was used. The Tables of critical values are developed at 5% and 1% level of significance by means of a simulation study.Applications of two other methods which are based on sample skewness and Kurtoses have been extended to detect the outliers in Moment distributions. The Tables of critical values are also generated for these two methods at 5% and 1% level of significance on the basis of a simulation study. The performance rates of four methods are found at various sample sizes by means of a simulation study. It is worth mentioning that methods ?1 and ?2 only indicates the presence of outliers in the data, while methods ?1 and ?2 not only identify the presence of outliers but also specify the particular outliers.