With Luka Modric still going strong at Real Madrid even at the age of 38, it's natural to wonder whether football players are enjoying longer careers in modern football. Karim Benzema won his Ballon d'Or at 34, Cristiano Ronaldo continues to thrive in the Saudi Pro League, and it's still hard to find any player better than Lionel Messi. Messi, who won his last Ballon d'Or at 34 and is the current holder as well as a World Cup winner, exemplifies this trend. Zlatan Ibrahimović played until he was 40, and other stars like Sergio Ramos, Franck Ribéry, Arjen Robben, and Manuel Neuer had successful careers into their late 30s. Even Ashley Young, despite not being young anymore, is still playing in the Premier League well into his 30s. But are these players just outliers, the exceptions that every generation has?

With Luka Modric still going strong at Real Madrid even at the age of 38, it's natural to wonder whether football players are enjoying longer careers in modern football. Karim Benzema won his Ballon d'Or at 34, Cristiano Ronaldo continues to thrive in the Saudi Pro League, and it's still hard to find any player better than Lionel Messi. Messi, who won his last Ballon d'Or at 34 and is the current holder as well as a World Cup winner, exemplifies this trend. Zlatan Ibrahimović played until he was 40, and other stars like Sergio Ramos, Franck Ribéry, Arjen Robben, and Manuel Neuer had successful careers into their late 30s. Even Ashley Young, despite not being young anymore, is still playing in the Premier League well into his 30s. But are these players just outliers, the exceptions that every generation has?

In this project, I will use two machine learning models, Random Forest and Logistic Regression, to predict heart disease. This is a simple model where I use all available variables to make the prediction. I won’t delve too deeply into the problem beyond the estimation part. In reality, establishing causal inference requires more subject expertise and looking beyond the data for analytics. However, the goal today is to demonstrate and practice running these two machine learning models.

Quarto is a powerful data analytics tool that Posit Inc. built-in RStudio. The main feature of Quarto is that it can seamlessly switch between R and Python to do data analytics. This article is actually based on the workbook that I created in Quarto.

This exercise presents how the sampling mean distribution with the increase in the size of the sample has a tendency towards normal distribution.

This document will proved why sample mean is an unbiased estimator of population whereas sample variance is a biased estimator.

This document is about how k-means can be used in R. In this document, I have clustered players from Fifa 20 based on their attributes. The cluster is than compared with the players actual position so check how the clustering worked.

This document provided simple step on how one can apply k-means on R.

Linear Regression and Modelling