Thread by @mdancho84

This used to be me when I was first learning linear regression. 😂

But here's what's changed for me. 🧵

#datascience #rstats #stats

I always thought it was funny how in the stats books, they'd always tell you of this magical P-Value level of 0.05.

You either reject (p > 0.05) or fail to reject (keep it when p <= 0.05).

So naturally, I'd do whatever I could to get my p-values under 0.05.

So what changed?

I started learning machine learning and actually seeing that my model performance would improve with features that had p-values greater than 0.05.

Wait, what?!

This magical p-value was actually costing me good information?!!!

Yup.

So fast-forward to today. I still use Linear Regression...

...But, I make more accurate forecasts and churn models using new algorithms like XGBoost & H2O.

And what's cool is these algorithms will help you.

These algorithms penalize bad features so we don't have to drop them cold-turkey style like with Linear Regression.

You just have to know how to use these algorithms.

Anyways, I guess what I'm saying is...

It took me painfully long to learn secrets like this. Like 5-years.

And, I don't want you to have to take EONS to learn too.

In fact, I'd like to help you.

I put together a free webinar - It's 40-minutes of training on the 10 secrets that took me 5 years to learn on my path to becoming a data scientist.

Literally what worked, and what mistakes to avoid in your path.

I cover all of it in one value-packed training.

What's your next step?

It's simple.

Just watch my free 40-minute webinar and take good notes (you'll thank me).

Watch here: learn.business-science.io/free-rtrack-ma…