JHU ADS 2020 Week 8 - Modeling Data

At the end of this lesson you will be able to:

• Define the central dogmas of prediction and inference

• Identify the key components of a modeling process (signal, systematic noise, random noise)

• Apply the steps in statistical modeling for data science

• Know how to use “wrong” models to get correct inference for specific trends

This week we (a bit belatedly!) talk about the “central dogma of statistics”

The “central dogma of machine learning”

And how to build models that account for signal, systematic noise, random noise - and analyst decisions! Don’t forget to tell your friends about JHU Advanced Data Science.