No abstract

This study introduces a new, better, class of ratio estimators for the estimation of population variance of the study variable by using the coefficient of quartile deviation of auxiliary variable. Bias and mean square error of the proposed class of estimators are also derived. The conditions of efficiency comparison are also obtained. Simulation and different secondary data sets are used to evaluate the efficiency of proposed class of variance estimators over existing class of estimators. The empirical study shows that the suggested class of estimators is more efficient the existing class of estimators for the population variance.

This research study is designed to develop forecasting models for acreage and production of wheat crop for Chakwal district of Rawalpindi region keeping in view the assumptions of OLS estimation. The forecasting models are developed on the basis of 15 years data from 1984-85 to 1998-99 then wheat area and production for next five years from 1999-2000 to 2003-04 is forecasted through the models and compared with the actual figures. After evaluating the accuracy of the models, final models are developed on the basis of 20 years data for the period 1984-85 to 2003-04. These linear models can be used to forecast wheat area and production of next five years. The Urea fertilizer, DAP fertilizer and manures plays a significant role to enhance the production of wheat crop. Number of ploughs in the wheat fields is significant factor to increase the production of wheat crop. Good rains in the month of October and November significantly contributes to increase the production of wheat crop and mean maximum temperature in the month of March is a significant factor to reduce the production of wheat crop.

This study is an experimental test done on the secondary data of banking sector of Islamabad Stock Exchange for year 2017 and applied different techniques on the given data record by using Generalized Extreme Value Distribution (GEV), Gumble Distribution (GBL), Generalized Pareto Distribution (GPD), Exponential Distribution (EXP), Gamma Distribution (GAM), Weibull Distribution (WBL) on the data of four banks Habib Bank, Allied Bank, Bank Alfalah and Askari Bank. This data is concerning the closing quotations and returns of four banks registered in Islamabad Stock Exchange. We try to fit different distributions on the data and founnd the best fit distribution. We estimated the parameters of each distribution and also find the standard deviations of each distribution by using R Language and find which distribution is the best fit distribution on the basis of standard deviation distribution. We analyzed that shape wise GEV is the most suitable distribution, scale wise EXP distribution the best and location wise the best one is Gumbal distribution. This article shows that the overall GEV is the best distribution to model correctly the data.

This research study is designed to obtain a more precise class of estimators of a population variance by taking advantage of relation between auxiliary variable and study variable. Here a class of new modified ratio type estimators of population variance by using coefficient of variation (CV), standard deviation, mean and median of auxiliary variable. Further empirical study is made to compare bias and mean square error (MSE) of proposed estimators with the existing estimators. Expressions for bias and MSE are obtained. Few secondary data sets are used to check the efficiency of proposed estimators of population variance.