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WHAT and WHY of Log Odds
The three main categories of Data Science are Statistics, Machine Learning and Software Engineering. To become a good Data Scientist, one needs to have a combination of all three in their quiver. In this post, I am going to talk about a Log Odds — an arrow from the Statistics category. When I first began working in Data Science, I was so confused about Log Odds. I would have questions like What is Log Odds, Why do we need them, etc.
When trying to understand any concept, I like to use the Divide and Understand strategy, i.e., break it into smaller pieces, understand their meanings separately, and then combine this knowledge to get hold of the concept as a whole. So here, let’s first learn what is meant by Odds and then try to work our way towards understanding Log Odds.
For the purposes of this explanation, let’s consider a scenario where I play 10 games of chess against an Artificially Intelligent (AI) system and 4 times I am able to beat it (I will be impressed by my chess skills if I am actually able to do that in reality).
Odds and Probability
As per our scenario, there are 4 times I am able to beat the system, so the odds of me winning the game are 4 to 6, i.e., out of total 10 games, I win 4 games and lose 6 games.