MS/M.Phil DQM (Economics and Qualitative Management

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    Effects of Social Applications on Students Academic Performance in Pakistan
    (UMT, Lahore, 2016) TEHREEM JAWAD
    Social 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.
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    YIELD FORECAST MODELING FOR WHEAT CROP USING AGRO METEOROLOGICAL DATA
    (UMT, Lahore, 2016) MUHAMMAD FAROOQ
    This 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.
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    A COMPARISON OF DIFFERENT WEATHER FORCASTING MODELS
    (UMT.Lahore, 2017) Zaheer Abbas
    In this thesis, we studied the performance of different statistical models and compare their forecast accuracy. In particular, we used multiple linear regression (MLR), seasonal autoregressive fractional integrated moving average (SARFIMA), and artificial neural network (ANN).
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    FACTORS EFFECTING ON STUDENTS ACADEMIC PERFORMANCE OF PAKISTANI SCHOOL'S CHILDREN IN THE SULTANATE OF OMAN
    (UMT.Lahore, 2017) Zameer Hussain
    Academic Performance of Students is a foremost function of any academic institution. The level of academic achievement is the measure to coined better one institution to the other. Several quantitative methods have been employed to measure and understand the different areas where the Academic Performance of the students is being affected. The study reflects the factors affecting Academic Performance of Students of Pakistani Schools in the Sultanate of Oman in which several independent variables were suggested to check the Academic Performance of Students. Factor analysis was used to determine the number of factors that are affecting the Academic Performance of Students of Pakistan school in Sultanate of Oman. Marks of English and Mathematics were created impact on Academic Performance of Students while Social Media, usage of Mobile games and watching TV were created negative impact on Academic Performance of the Students of Pakistani schools in Sultanate of Oman.
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    Agent Base Simulation Fashion Retail Chain
    (UMT.Lahore, 2017) Azam Saeed
    This research develops a multi-agent simulation model for fashion retail supply chain. Intelligent agents are designed using SQL to performed key roles of supply chain management for fashion retail.
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    The Impact of Economic Performance, Democracy and US Aid on Terrorism
    (UMT.Lahore, 2017-02) Muhammad Saqib Maqsood
    This research work is an attempt to examine the economic and political factors that can have a significant impact on terrorism within Pakistan. We captured data for Inflation, Investment, Educational Expenditures, Trade, Democracy and US Aid to Pakistan. Autoregressive Distributed Lag Model (ARDL) along with granger causality testwas applied to analyze short-run, long-run impact coefficients and direction of granger causality among these variables. The results suggest that increasing educational expenditures and investment in the country are increasing terrorism in Pakistan. While on the other hand, decreasing inflation and increasing trade can dampen the intensity of terrorist attack. More US Aid directed towards counter-terrorism policies and non democratic regimes were also found to have increased terrorism intensity.
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    Income Inequality Comparison Through Parametric Modeling
    (UMT.Lahore, 2017-02) Hussnain Abbas
    This study takes into account the determination of income inequality by non-parametric and parametric approach and comparison of the two techniques in the context of Multiple Indicator Cluster survey (MICS) data of Punjab for the years 2007-08 and 2013-14.
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    Mixture Regression Estimators of Population mean under Stratified Random Sampling
    (UMT.Lahore, 2017-03) Madiha Fatima
    In this study, Mixture Regression Estimators for single phase sampling under stratified random sampling have been proposed, by incorporating the simultaneous use of information on auxiliary variables and attributes. The estimators have been proposed for three different cases and their mean square errors have been derived mathematically. A Simulation study has been done by using simulated data, to check the distribution of proposed estimators. This study shows that proposed estimators, seems to follow the normal distribution. An empirical study has also been done by considering two natural data sets. Mean square errors (MSE’s) for the proposed estimators have also been computed and Efficiency comparisons made with single phase mixture regression estimators proposed by Moeen et al. (2012). On the basis of MSE’s computed through simulation and empirical studies, it is to be concluded that proposed estimators are more efficient than that of estimators proposed by Moeen et al. (2012) for simple random sampling.
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    Mixture Regression cum Ratio Estimators of Population mean under Stratified Random Sampling
    (UMT.Lahore, 2017-03) Kanwal Iqbal
    In this thesis, single phase Mixture Regression cum ratio Estimators by using auxiliary variables and auxiliary attributes simultaneously have been proposed under Stratified Random Sampling. Special cases of the estimator are discussed and their mean square errors are also derived mathematically. A simulation technique has been used to observe the properties of proposed estimator which shows that the distribution of proposed estimator approximately normal. . An empirical study has been conducted by incorporating quantitative and qualitative characteristics in the form of auxiliary attributes and variables simultaneously to compare the performance of proposed estimator. Comparisons are made with Moeen et al. (2012) single phase mixture regression cum ratio estimator under simple random sampling. It has been found that the mixture regression cum ratio estimator using multiple auxiliary variables and attributes simultaneously under stratified random sampling is more efficient than Moeen et al., (2012) mixture regression cum ratio estimator under simple random sampling.
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    Exploring and Comparing Factors Affecting the Reading Abilities of Grade-III Students
    (UMT.Lahore, 2017-05) Sidra Mujahid
    In this study we investigate different factors affecting the reading abilities of Grade III students’ in Army Public Schools of Lahore. Data has been collected from 10 APSACS Schools. A sample of 299 respondents has been drawn using probability proportional to size sampling technique. Ordinal Logistic Regression analysis has been used to explore the factors affecting students’ reading achievement. It is concluded that occupation, facility library and comments on pictures have a significant effect on students’ reading achievement.
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    Exploring the Factors Affecting the Purchase of Different Mobile Phone Brands
    (UMT.Lahore, 2017-06) Madiha Javed
    In this study we explore the effects of various factorsin selecting a specific mobile brand by students of different universities of Lahore.Multinomial logistic model has been utilized to check significance and effect of the variables. Results revealed that gender, age, discipline of study, job status, no. of family members, no. of employed family members and mobile phone price has turned out to be statistically significant indicators for selection of mobile brand. Gender, age, discipline of study, job status and no. of family member have positive effect on selecting mobile brands such as Samsung, Nokia, LG, Huawei and Others. While no. of employed family members and mobile phone price have negative effecting on selecting these brands.
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    Performance Assessment of some Existing and New Ridge Regression Estimators
    (UMT.Lahore, 2017-10-16) Himmad khan
    An important assumption of the multiple linear regression model is that the regressors should be independent, which is violated in practice. Due to violation of this assumption, the problem of multicollinearity occurs and results into unreliable statistical inference for the model parameters. To cope this, several biased estimation techniques, including ridge regression, have been proposed in the literature. In ridge regression, the key problem is to estimate the ridge parameter and there are several methods in the literature for this purpose. In this thesis, we propose six different shrinkage estimators, named as HMS1 to HMS6 and further compare them to some existing methods, like HK, KMS, KSM, KMED and KGM. We use Monte Carlo simulations to assess the performance of different estimators assuming the mean square error as a performance comparison criterion.
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    Relationship between Ease of Doing Business and GDP
    (UMT.Lahore, 2017-11-11) Faiza Shahid
    Business is of immense importance for the life of a country. Economy of whole country depends on its business. Each Govt. is introducing new policies and programs to increase business in country as well as to make easiest to do business for investors. Many factors are considered for doing business in any country such as its market, currency rate of country, demand of product or service in country, costs, inflation rate, climate and culture etc. In this paper, we identified the difference in Mean of Ease of Doing Business in Muslim and Non-Muslim countries by using the ANOVA models. Moreover, we not only described the effect of Gross Domestic Product on Ease of Doing Business, but we also considered the social and environmental factors too while considering the relation of business and GDP. Moreover, we extended our study by showing the path by Which GDP effect EODB. We used the measure of Social Progress index for social and environmental factors, and we checked the mediation effect of Social Progress Index in relation of Ease of Doing Business and Gross Domestic Product. We used the bias corrected mediation technique for testing indirect effect.
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    Relationship between Ease of Doing Business and GDP
    (UMT.Lahore, 2017-11-11) Faiza Shahid
    Business is of immense importance for the life of a country. Economy of whole country depends on its business. Each Govt. is introducing new policies and programs to increase business in country as well as to make easiest to do business for investors. Many factors are considered for doing business in any country such as its market, currency rate of country, demand of product or service in country, costs, inflation rate, climate and culture etc. Culture of Muslim and Non-Muslim countries is very different due to many factors such as finance system of Muslim countries, consumption pattern of different things, concept of interest, social culture, religious holiday, weekend days, economic role of women, joint family system and sharia etc. In this paper, we identified the difference in Mean of Ease of Doing Business in Muslim and Non-Muslim countries by using the ANOVA models. Moreover we not only described the effect of Gross Domestic Product on Ease of Doing Business but we also considered the social and environmental factors too while considering the relation of business and GDP. Moreover we extended our study by showing the path by Which GDP effect EODB. We used the measure of Social Progress index for social and environmental factors and we checked the mediation effect of Social Progress Index in relation of Ease of Doing Business and Gross Domestic Product. We used the bias corrected mediation technique for testing indirect effect.
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    Kumaraswamy Marshall Olkin Logistic Exponential Distribution
    (UMT.Lahore, 2018) SANA JAWAD
    We are presenting this research to propose Kumaraswamy Marshall-Olkin Logistic-Exponential Distribution. It has five parameters. Several statistical properties including reliability, moment generating function, quantile function are derived. Furthermore the derivation of entropy and order statistics expressions for the proposed distribution is also part of this study. The approach of ML estimation is used for estimating the unknown. The goodness of fit statistics Anderson Darling, Cramer Von Mises and Kolmogorov Smirnov statistics were used as a goodness of fit measures. An empirical work is conceded to examine the behavior of the new distribution. In conclusion a real life application of this purposed Kumaraswamy Marshall-Olkin Logistic-Exponential distribution is stated.
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    Influence of Socio Economic Factors on Forests Depletion
    (UMT.Lahore, 2018) Iqbal Hussain
    In this study we have explored some important socio-economic factors affecting the forestry area in Khyber Pakhtunkhwa. These factors include real agriculture growth, real manufacturing growth value, population growth, cultivated area, irrigated area, livestock population etc. The Multiple time series linear regression technique has been used to achieve the objectives of the study. The data for the study consists of socio-economic variables taken from various sources including Pakistan Economic Survey, Pakistan Energy book etc. for the years 1972-2000.
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    A Study on Economic determinants Affecting Child Labour
    (UMT.Lahore, 2018-06) Arshad Hameed
    This study provided the main influence factors on child labour by using World Bank data of 112 countries. The strategic way of low and above average of child labour techniques were used to check the more significant behavior of the study child labour. The significance relationship between the child labour and FDI, Per Capita GDP, Inflation, percentage of employee from industrial and Literacy rate. All the data were analyzed by using SPSS statistics version 23 and then analyzed for the significant outcomes. Child Labour and predictors was analyzed by t-test, Leven test, and binary logistic regression to check the significant effect. The relationship GDP per capita, Inflation, Literacy rate has significant relationship with child labour. While the FDI and industrial have insignificant effect. The t-test was used to check the equality between two groups of child labour below average and above Average.
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    The Mediating effect of Foreign Direct Investment (FDI) and Social Progress Index (SPI) between Population and Global Hunger Index (GHI)
    (UMT.Lahore, 2018-06) AQSA LARAIB
    In this research, we propose a model to explore the factors causing Global Hunger Index (GHI). The model studies the role of Population in predicting GHI while incorporating FDI and SPI as mediating variables. The data set for the analysis based on these variables are taken from on line World Bank data sources. The Hayes’ Process version 13 mediation tool and model 4 is selected to perform the Multiple Regression Analysis. The results indicate “Partial mediation effect” when FDI is taken as mediator between Population and GHI. There seems to be “Full mediation” when SPI is considered as the second mediator between Population and GHI. The proposed model satisfies the regression assumptions.