استنباط احکام میں حضرت عائشہ کا منہج قرآن کریم کی روشنی میں

In this article an effort has been made to describe Hazrat ‘฀ishah (R. A) ’s methodology of derivation of Ahk฀m from Holy Quran. Holy Quran and Sunnah of Holy Prophet (S. A. W) is basic source of Islamic Shar฀‘ah. Hazrat ‘฀ishah Sidd฀qah (R. A) was the wife of the Holy Prophet (S. A. W), and the daughter of Hazrat Ab฀ Bakr (R. A). She spent her time in learning and acquiring knowledge of the two most important sources of Islam, the Qur'an and the Sunnah of His Prophet (S. A. W). Hazrat ‘฀ishah (R. A) narrated 2210 Ah฀d฀th out of which 174 Ah฀d฀th are commonly agreed upon by Bukh฀ri and Muslim. She was an ardent and zealous student of Islamic jurisprudence. She has not only described Ah฀d฀th and reported her observations of events, but interpreted them for derivation of Ahk฀m. Umm Al-Mu’min฀n Hazrat ‘฀ishah (R. A) is a great scholar and interpreter of Islam, providing guidance to even the greatest of the Companions (R. A) of the Holy Prophet Muhammad (S. A. W). She has not only described Ah฀d฀th and reported her observations of events, but interpreted them for derivation of Ahk฀m. Whenever necessary, she corrected the views of the greatest of the Companions of the Holy Prophet (S. A. W). It is thus recognized, from the earliest times in Islam, that about one-fourth of Islamic Shar฀‘ah is based on reports and interpretations that have come from Hazrat ‘฀ishah (R. A). As a teacher she had a clear and persuasive manner of speech. Hazrat ‘฀ishah (R. A) is a role model for women. She taught Islam many people. She was an authority on many matters of Islamic Law, especially those concerning women.

Some New Families of Continuous Distributions Generated from Burr Xii Logit

This thesis is based on six chapters. In these chapters five new families of distributions are introduced by using the Burr XII distribution. In Chapter 1, a brief introduction of the existing families of distribution, the objectives and organization of this thesis are presented. In Chapter 2, Generalized Burr G family of distributions is proposed by using the function of cdf − log[1 − G(x)]. In Chapter 3, Marshall-Olkin Burr G family of distributions is introduced by using odd Burr G family of distributions used as generator proposed by Alizadeh et al. (2017). In chapter 4, odd Burr G Poisson family of distribution is introduced by compounding odd Burr G family with zero truncated Poisson distribution. In Chapter 5, a new generalized Burr distribution based on the quantile function following the method given by Aljarrah et al. (2014). In Chapter 6, Kumaraswamy odd Burr G family of distributions is introduced using odd Burr G family as a generator. The mathematical properties of these families are obtained, such as asymptotes and shapes, infinite mixture representation of the densities of the families, rth moment, sth incomplete moment, moment generating function, mean deviations, reliability and stochastic ordering, two entropies, Renyi and Shannon entropies. The explicit expression of distribution ith order statistic is also obtained in terms of linear combination of baseline densities and probability weighted moments. Model parameters are estimated by using the maximum likelihood (ML) method for complete and censored samples. Special models are given for each family, their plots of density and hazard rate functions are displayed. One special model for each family is investigated in detail. Simulation studies are also carried out to assess the validity of ML estimates of the model discussed in detail. Application on real life data is done to check the performance of the proposed families.