Practical Statistics for Data Scientists

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Practical Statistics for Data Scientists

1. Exploratory data analysis

Elements of structured data

Estimates of location

Estimates of variability

Exploring the data distribution

Exploring binary and categorical data

Correlation

Exploring two or more variables

2. Data distributions

3. Statistical experiments

4. Regression

5. Classification

6. Statistical ML

7. Unsupervised learning

3. Statistical experiments

A/B testing

An experiment with two groups to establish which is superior

Why have a control group?

In a properly designed A/B test:

Subjects are randomized to either treatments

Need to collect data on treatments A and B in such a way that any observed difference between A and B must be due to either:

Random chance in assignment of subjects

A true difference between A and B

Must establish a single test statistic before conducting the test, otherwise leave room for researcher bias

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Why just A/B? Why not C, D…?

If testing which is the best out of multiple possible conditions, use

multi-arm bandit

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