Digital Minimalism in Data Science

At the beginning of the New Year, I did something that was cliche. I read books about productivity. These books were Cal Newport's Digital Minimalism and James Clear Atomic Habits. I realized I was just busy but not getting the results that I wanted.

So, I decided to do an experiment this month. Practice digital minimalism while improving my data science skills. I’m not using R or Python this month. Only going to rely on books or journal articles to learn about how to work with data.

1. Get your reps in

In order to get better at something, you have to get your reps in. Whether you are training to get a six-pack or learning how to play the guitar. In order to get better at something you just need to do it a lot. One lesson that I learned from Atomic Habits is that if you want to create a habit make it attractive. So, I’m going to review my statistic fundamentals with The Humongous Book of Statistics Problems by Michael Kelley. It's not a dense book and it has a lot of practice problems inside of it. I’m also going to use Schaum’s Outline of Beginning Statistics for additional practice.

2. Just want to strip things to their core

Right, I feel like I’m more worried about the syntax of my R or Python code than understanding what the data is saying. It's like I’m trying to learn how to write before learning how to read. Yes, it is possible to write before learning how to read. But at the end of the day, it would be just lines on a piece of paper. Not you conveying an idea to someone else. Yes, I can wrangle data using select, filter, arrange, mutate, and summarise. Whats the point of knowing those functions if you don’t know when to use Anova or a chi-square.