There are a lot of engineers who have never been involved in the field of statistics or Data Science.
But in order to build data pipelines or rewrite produced code by Data Scientists to an adequate, easily maintained code many nuances and misunderstandings arise on the engineering side. For those Data/ML engineers and novice Data Scientists, I’ve made this series of posts.
I will try to explain some basic approaches in plain english and, based on it, explain some of the basic concepts in Data Science.
The whole series topics:
- Bayes theorem
- Probability distributions
- The Central Limit Theorem and Sampling
- Demystifying hypothesis testing
- Data types in Data Science
- Descriptive and Inferential Statistics
- Exploratory Data Analysis
Follow to continue conversation series.