Semester 2

Projects

Title: Energy Consumption model for Low Energy Buildings

Synopsis: The main idea behind this project is to fit a Linear Regression model to find the Energy Consumption Data for Low Energy Buildings of Belgium gathered from “m-bus” energy meters using temperature and humidity data gathered from “ZigBee” IOT temperature sensors and the Weather data from Local Weather Station in Chèvres (Belgium).

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Supervisor: Mr. Taranga Mukherjee 

Title: Car Price Prediction using Linear Regression Model

Synopsis:. An automobile company aspires to enter the market by setting up their manufacturing unit and producing cars locally to give competition to their counterparts. Specifically, they want to understand the factors affecting the pricing of cars. The company wants to know: · Which variables are significant in predicting the price of a car? · How well those variables describe the price of a car Hence , we are required to model the price of cars with the available independent variables (covariates/contributing variables). It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market.

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Supervisor: Mr. Taranga Mukherjee 

Title: Holistic Approach towards Analyzing Customer Perception towards Life Insurance products: An empirical study in West Bengal

Synopsis:. To cope with the above challenges and to improve customer satisfaction the insurance companies have to find ways to make their services more tangible. Through this study the researcher aims to provide the insurance service providers an insight of the scenario so that they can reframe their targeting strategies and become proactive in approach. To maximize the certainty and to minimize the uncertainty is the main focus of the study.

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Supervisor: Dr. Sankar Prasad Mondal

Title: Statistical Study of Williamson Fluid in boundary layer  flow.

Synopsis:. The main objective of this dissertation is to focus on a numerical study on the unsteady boundary layer flow of MHD Williamson fluid in the stretching boundary layer thickness. A mathematical model which resembles the physical flow problem has been developed. Similarity transformations are used to convert partial differential equations (PDEs) into a system of nonlinear ordinary differential equations (ODEs). The resulting system of ordinary differential equations (ODEs) is solved numerically by using spectral quasilinearization methods, which shows an excellent agreement. Numerical values of skin friction coefficient and Nusselt number (heat transfer rate) are also computed. The effects of different physical parameters on the correlation coefficient are discussed in detail. Also, the utilization of statistical tools like probable error and linear regression for the analysis of the results adds to the novelty of the study.

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Supervisor: Dr. Hiranmoy Mondal

Title: An investigation of latent structure regarding the purchase of mobile phone and its validity through SEM.

Synopsis: In market research analysis, high-dimensional data is available more often, making it difficult for researchers to visualize and analyze the data. In our present study, an overview of factor analysis has been explored and applied the same to extract the important information by investigating the main factors affecting a consumer’s choice of mobile phone. A set of related parameters were identified and corresponding data has been collected through Online Questionnaire. Using Exploratory Factor Analysis (EFA) it has been possible to determine meaningful underlying constructs or factors which capture a reasonable proportion of the total variance. The attempts have been made to find out a lesser number of factors responsible for customers' choice regarding the selection of mobile phones without the loss of extra variance. Also, the reliability of the factors has been checked using Confirmatory factor analysis.

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Supervisor: DR. Prasanta Narayan Dutta, Dr.Banashree Sen & Ms. Anwesha Sengupta