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Item Effects of Social Applications on Students Academic Performance in Pakistan(UMT, Lahore, 2016) TEHREEM JAWADSocial applications is the act of the growing the quantity of the ones business and social contacts by making associations through people frequently through social applications, for example, facebook, likendln, imo, twitter, whatsapp, and viber and so on. The fame of the social applications has quickly expanded in the recent years. Social applications gives numerous sorts of services and advantages to its clients like helping them to attach with new people groups, offers conclusions with like personality individuals on the web. In any case, the principle disadvantage of the chat rooms was that you may not know the individual with whom you are collaborating with. The presentation of profiles on social applications sites permitted individuals to know more information about a person before they interface with them. The purpose of our research is to explore the significant factors which have effect on the student’s academic performance. The study of this research is quantitative in nature. The target populations for this research are the university students of the Lahore. The sampling method which is utilized for this exploration is the stratified random sampling. As indicated by the rule of the hair & Anderson our total sample size for this research is 245. Then STATA has been used to analyze the collected data. Survey results were analyzed using the Multiple Linear regression. The results show that the significant and harmful association between the time spent on the social package and the academic execution. Student’s characteristic, time management, and predictor behavior is the positive impact on the academic execution as the time management enhance the student’s academic performance is also increases.Item YIELD FORECAST MODELING FOR WHEAT CROP USING AGRO METEOROLOGICAL DATA(UMT, Lahore, 2016) MUHAMMAD FAROOQThis thesis explores the possibility of using remote sensing images and its derived products, Normalized Difference Vegetation Index (NDVI), to assess and measure wheat yield potential. Panel regression models were developed for the Gujranwala division at different stage of spatial aggregation. Through the panel regression analysis, the study identified the relationship between the crop vegetation over the growing period and the final crops yield. The vital goal of the research is to inspect whether the NDVI model can generate precise and timely yield forecasts.The present study primarily focuses on the variation of crop yield through NDVI based panel regression analysis is used as a tool to achieve this objective. The NDVI model is used to represent crop vegetation density or greenness (reflectance of all agro metrological parameter) of the vegetation cover. It proves that, crops yield can be predicted more effectively and accurately by using NDVI base model as an alternative tool against the conventional models. The Redundant and Hausman test which guides about the fixed effect model is suitable in this study. The NDVI base fixed effect model fits the crop yield data extremely well, with high R-square value at about 90%. The results suggest that NDVI for the month of January, February and March were ideal for wheat yield assessment.Item Determinants of Inflation A case study of Developing and Developed Countries(UMT, Lahore, 2016) Sadia GhaffarItem CONSUMER CHOICE TOWARDS MODERN AND TRADITIONAL STORESWHILE BUYING FMCG(UMT, Lahore, 2016) Nazia Akram