Analysed the data of around 200,000 online chess games hosted on the lichess.org platform. The game data has been extracted from the official database of the Lichess website.

Constructed a credit scoring model, based on logistic multiple regression, for acceptance of credit based on five predictors namely age, dependent income, indicators of home ownership, self-employment and the number of notices of insolvency of an individual within a fixed time period.

The historical data (Election Prediction Questionnaire) of victories of presidential party and victories of opposition party along with the answers to 12 questions are used as the dataset for analysis and research purposes. The data was used to train mathematical models such as Decision Tree, KNN, Fisher Discriminant and clustering.

This project aims at answering the question “Does the psychological predisposition to nicotine usage
exist?”. Different methodologies that were implemented were one attribute classifier, KNN algorithm with K value as 1 & 3 and compared with Fisher Linear Discriminant method.

Performed time series analysis on four different time series such as JPMorgan Chase & Co., Paypal, Visa and Wells Fargo & Company. An attempt was made on predicting the future prices of the time series based on the pattern observed.

The data of recent and lapsed internet users and non-internet users of the past few years in the UK was processed and analysed. This project aims to evaluate if it seems profitable project for a market leader in Asia in Telecommunication sector to initiate its operations in the United Kingdom along with suggestions on the groups of people to focus on for visible growth

The CoViD-19 data of countries such as Brazil, France and Italy were analysed. Methodologies such as Predictive Analysis for logistic models, SIR Models, Theory of GAS and Modified SIR model were implemented and compared for better understanding.

The road safety data of UK was analysed with emphasis on casualties by answering questions like casualties across age bands, casualties under different light and road conditions, Casualty trend across days of weeks for different vehicle types.