If you are someone who recently visited webpages of the statistics department of a top north American universities, you might have come across these three terms, Mathematical Statistics Computational Statistics Applied Statistics. This is especially relevant if you are looking into the information on the graduate programs. If you have…

If you are an aspiring data scientist/analyst, and if you are wondering where to start, let me give you some encouragement. There are thousands of blogposts, videos, podcasts regarding which programming language that data analysts should learn. It seems that Python is the popular choice but there is a significant…

Can we tell whether team or player performances are different? Is there a way to use scientific approach to get the answer? In the era of big data, it is easy to crunch numbers, create great visualizations, and come up with KPIs to show the difference between teams or players…

Data visualization is important in professional setting. It has been around for a long time. Even before the appearance of data viz software and tools like Tableau, people used Excel and PowerPoints to produce spectacular dashboards and reports. Regardless of the tool, there are always a few simple but important…

Sports analytics have seen rapid rise in recent years due to availability of large amount of data. Books and movies like Moneyball have glorified the impact of data driven decision making in different sports. Soccer is no different. Teams and analysts can now apply data analysis techniques to improve results…

Feature selection is an important topic in machine learning. It is relevant for both supervised and unsupervised problems. At this moment there are probably thousands of articles on the internet on different aspects of feature selection. So, I am not going to repeat that by discussing what feature selection is…

Knowingly or unknowingly we deal with groups all the time when we work with datasets. Companies do it when they want to segregate their customers into different groups so that they can position their products. Universities are grouped according to their rankings, quality of research, etc. Employers group their employees…

Objective of the project: Transform the JSON files to dataframes to facilitate easy exploration and analysis. Automate the data wrangling steps so that they can be applied to multiple datasets. Develop query methods to help producing aggregated data by team or player. Adopting object oriented programming to help managing the…