Data Analysis In The Real World: Our Professors Lied To Us

Haha! What a title!

I was inspired to make this series because in my job as a statistician — I’m realising that real world statistics isn’t really “covered” in my undergraduate statistics classes. Some things you realise your professors completely didn’t cover — others you realised that your professors hinted at, but didn’t explicity tell you the terms for what you were doing.

This series is a collation of the “Eureka!” moments I had in my job — learning, re-learning, and un-learning some of the things that I covered in school. I designed this series in a beginner friendly manner that be useful for those who want a taste of Data Analysis in the Real World (Industry setting).

The contents of this series are as follows:

1. Statistics beyond University: How Academic Statistics differs from Industry Statistics

2. Time Series Analysis Made Simple: From Regression to Markov Chains

3. Time Series Forecasting: An Oversimplified Guide to Long Short Term Memory Models

4. My R² was Negative: Doing Linear Regression in Python (Statsmodels Library)

5. Removing Outliers: What happens to your p-value?

6. Transformation of Data to Save Your Model

7. Learn Python for Data Analysis: Manipulation, Visualization, Statistics & Machine Learning (Paid Resource)

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