خواجہ عبدالرؤف عشرت لکھنوی
خواجہ عبدالروف عشرت، لکھنؤ داروغہ حیدربخش کی مسجد کے نیچے کتابوں کی ایک چھوٹی سی دوکان پر بیٹھا کرتے تھے، مگر خدا جانے کیا بات ہے یہ چھوٹی سے معمولی حیثیت کی دوکان نصف صدی تک لکھنؤ کے اہل علم و ادب کا مرکز بنی رہی، اور میں نے بھی چالیس برس اس چھوٹی سی دکان کو اسی طرح علم و ادب کے قدرشناسوں کا مرکز دیکھا، اس وقت جب لکھنؤ کا چوک بجلی اور گیس کی روشنیوں سے جگمگارہا تھا یہی دکان تھی جس پر پرانا مٹی کا چراغ جلا کرتا تھا، اور دنیا کو وضعداری کی روشنی دکھاتا تھا، افسوس کہ زبان و ادب کا یہ ٹمٹماتا ہوا چراغ بھی بجھ گیا۔
خواجہ صاحب گو خود غیر معمولی شاعر نہ تھے، مگر لکھنؤ کے بڑے بڑے شاعروں کی صحبت اٹھائے تھے، بحرؔ مرحوم کے شاگرد تھے، نظم سے زیادہ نثر لکھتے تھے اور لکھنؤ کی راجدھانی اور لکھنؤ کے جانعالم کی کہانی ان کا خاص موضوع تھا، لکھنوء کی بول چال اور محاوروں اور روزمرہ کو بخوبی برتتے تھے، نیک مزاج، وضعدار اور قناعت پسند تھے، اﷲ تعالیٰ مغفرت فرمائے۔ (سید سلیمان ندوی،جولائی ۱۹۴۰ء)
It would be essential to know the pre Islamic economic conditions first, then it would be better to know that what are the Islamic principles regarding trade and economics. This would make us understand the Islamic principles fully; also it would help us to comprehend the nature of Arabs who were the same people who after coming into the fold of Islam agreed to lay down their lives for the Islamic cause. Keeping this in view, we can precise how much Islam advocates the truth and dignity for individual and business. Pre Islamic era was a dark period. Arabs had limited sources of Income and they relied upon the piracy and loot and plunder. In Dark era poets boasted Arabs loot and glorified it in their poetries. No one can deny that Arabs had bravery in their blood, and they conceive courage from their mother's womb. They used to loot money from affluent in the day time and gave away to the needy who used to boast them in their poetries. This Article discusses the Arab’s economic conditions in pre-Islamic Era.
Most of the data sets belonging to the real world contain observations at the extremes that might not be in conformity with the remaining data set. These extreme observations known to be outliers might have positive or negative effect on the data analysis like regression estimates, forecasting and ANOVA etc. Outliers are powerful tools to identify the most interesting events of the world in cross sectional data and historically important events can be picked by detecting outliers in time series data sets. Numerous outlier detection techniques have been proposed in the literature. This study provides a survey of these techniques and their properties. Most of these techniques work well under the assumption that data come from a symmetric distribution and these techniques fail to work in skewed distributions. Because of this limitation, Hubert and Vandervieren (2008) proposed a technique for outlier‟s detection in skewed data sets. Our thesis presents a new technique to measure robust skewness (SSS) and a new outlier detection technique (SSSBB) for skewed data distributions. The study shows that the proposed technique measures skewness more accurately than existing techniques and the proposed technique for outlier‟s detections works better than Hubert‟s technique on a class of theoretically skewed and symmetric distributions. The study also compares the technique with other established outlier detection techniques in the literature. This study uses simulation technique for computer generated distributions and some real data sets for comparison purposes. The study also analyzes real life data sets and compares the baby birth weight data and stock returns, both of which are known to be skewed. These results will help us in making a choice of appropriate outlier detection technique for skewed data sets for different sample sizes which might be helpful in identifying underweight babies.