Summary of Article
In an article written by Henry Hinnefeld, he describes a problem he faced in his childhood and how he decided to solve it as an adult with his newfound expertise(can find the article here). He and his friends played Mario kart all the time when they were kids and he wanted to know what the optimal combination of characters/karts/tires was to have the best chance of winning in the game. First, he classified the characters into 7 classes and then ranked each of those classes based on 5 factors – weight, speed, acceleration, handling, and traction. He then assumed that speed and acceleration were the most important in Mario kart to win the game so he only focused on those two categories from now on. He then did the same thing with the tire and the body of the vehicle that the character rides in. After, he took all of that data and plotted it on a Pareto Frontier (more commonly known as PPF or PPC). Finally, he found the combinations that lie on the Pareto Frontier because those are the best combinations according to the data. In case you are wondering what the insights were from his analysis(I know I was) here they are:
My Take
This was a really fun article to read. The reason being Hinnefeld took data and put it into something more atypical. This really showed me that data can be used for anything. When I think of data being used I used to think of big sectors of the economy like finance or tech, but now I have realized that data can be used anywhere from those big sectors to something as simple as finding the optimal combination for a character in a childhood video game. The article was also very well written and the author did a really good job explaining the concepts in a really reader-friendly way. One of the ways he did this was the article showed graphs and tables of the analysis process so that way the reader got a feeling of how it was to actually do the analysis and where he got his claims from. His graphs/tables and the transparency of his process really added to his credibility for both his insights and him as a data analyst.
Conclusion
All in all, this article was a really interesting and fun one. It introduced me to a new view on the applicability of data and how it can really be used for not just corporate purposes it can also be used for something as simple as insights on how to win your favorite childhood video game. The author did a really good job explaining the concepts and backing up his claim with graphs and tables from his analysis which not only made the entire article easier to read and digest but also added to his credibility both for his insights and himself as a data analyst. Overall it was a really good article and I definitely recommend you read it(the article can be found here)!!