Projects

Statistical Analysis using R

The personalized dataset is used to find out answers to three questions a) are there differences in the average study times for students in different analytics teams? b) is the distribution of days studied more than 3.13 hours (average daily study time of students from McGill University) the same for students in the different analytics streams? c) how does your study time change over time?

These questions are answered using statistical analysis in R markdown where ANOVA is used to compare different study times, chi-square tests are used for comparing the distribution of study time by program streams and time series analysis is done to show how personal study time change over time. The adjoining link will download the R markdown file.

statistical analysis, ANOVA, time series, chi-square test

Data Analysis using Python

This project, comparing the average heights of males and females in each country, is done as part of the Cambrian College course where the average heights of males and females are compared in each country using Python programming language. The objective of the analysis is to check the countries where the tallest and smallest males and females across the world are located. This was a fun exercise done for information purposes only and realizing the power of Python programming language to do such a kind of exploratory analysis. For this analysis, I used NumPy, SciPy, Pandas, Matplotlib, and Seaborn Python libraries. The report link is provided.

Interactive Dashboard using Microsoft Excel

The adjoining dashboard is designed as part of the project done with a UK-based school where grade 10 students were given a 4 weeks course on yoga and meditation. After the completion of the course, students were asked to fill up a survey to assess their opinion about the course and their general mindset after attending the seminar. The results of the study are then tabulated in an interactive excel dashboard to present to the school management. The dashboard uses the pivot table feature of excel sheet and then a single slicer is used to control all the charts in an interactive way.

Screenshot of excel intreractive dashboard for a school wellness seminar

Interactive Dashboard using Power-BI

The adjoining dashboard shows top US oil producing states. The interactive dashboard when chosen a particular US state shows proven oil reserves, acquisitions, adjustments, proved reserves, sales and estimated production in million barrels for each of the state. The dashboard is prepared in MS Power-BI application.

Infographic using Canva

The adjoining infographic is prepared using canva which shows the information about the global cigarette industry. The infographic shows the visual representation of the information. It uses a variety of elements like pictures, graphs, texts, icons, charts, and diagrams to convey the message at a glance. The infographic uses all three parts visual, content, and knowledge to convey the message. The infographic is prepared using the canva template.

Interactive Gradebook

A comprehensive interactive grade book is designed for a college professor to track the class's progress and any individual students' grades. The interactive grade book is designed in MS Excel using pivot tables, slicers, and hyperlink features. The data is entered at a few places in the datasheet for each type. The data is then collected in a master sheet using LOOKUP functions and aggregate functions. The interactive dashboard shows one for the entire class and the other for individual students.

500-ppm 'S' Gasoil Production

This project was undertaken to convert the refineries' export Gasoil market to 500-ppm 'S' Gasoil. The refinery was producing and marketing some 0.2% Gasoil but due to customer retention and better margin, the refinery decided to convert all its export Gasoil market to 500-ppm Gasoil. The study was done on a global linear programming model Aspen Tech PIMS. The project was successfully implemented. The brief summary is below:

The new Gasoil hydrotreater (HT) capacity was maximized to generate more low Sulphur Gasoil while the old Gasoil HT was limited in its capacity.
One of the residue treaters was converted to a diesel hydrotreater to generate more low Sulphur Gasoil.
Refinery tankage allocation was changed to accommodate more low Sulphur Gasoil.
The total economic impact was US$ 60 million (at 2016 prices).