Because of 3 simple statistical concepts: survivorship bias. expected value. and hot-hand fallacy.The house always wins. We all know this phrase. But this is more than a phrase. This is a simple, mathematically proven fact. And you’ll only have to know three statistical concepts to see why the house always wins.
You are at the casino. The roulette wheel is spinning and the ball is bouncing. Bounce, bounce, bounce, you smile: “it’s red!” And then it bounces one more. No, it’s black! You lose everything again and go home with empty pockets.
Well, I hope you won’t — because you don’t go to casinos, you don’t buy scratch tickets, you don’t play the lottery or any gambling game in general.
Why? Because these games are designed to make you lose money.
And in this article I’ll tell you why. (Check out the **[podcast](https://anchor.fm/data-science-podcast/episodes/Why-You-Shouldnt-Go-to-Casinos----3-Statistical-Concepts-eju3im) or [video](https://www.youtube.com/watch?v=MkfPALtnDG8) version of it, too!)**
The house always wins. We all know this phrase. But this is more than a phrase. This is a simple, mathematically proven fact. And you’ll only have to know three statistical concepts to see why the house always wins.
These three statistical concepts come up often in data science projects, too. So if you are wondering why I’m talking about gambling on a data science channel, rest assured, you’ll be able to take advantage of this knowledge in your data science career, too.
Anyways, three statistical concepts.
Let’s start with the first one.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
Statistics for Data Science and Machine Learning Engineer. I’ll try to teach you just enough to be dangerous, and pique your interest just enough that you’ll go off and learn more.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...
The List of Top 10 Lists in Data Science; Going Beyond Superficial: Data Science MOOCs with Substance; Introduction to Statistics for Data Science; Content-Based Recommendation System using Word Embeddings; How Natural Language Processing Is Changing Data Analytics. Also this week: The List of Top 10 Lists in Data Science; Going Beyond Superficial: Data Science MOOCs with Substance; Introduction to Statistics for Data Science