Exploratory Data Analysis - Experimental Design
About
An introduction to the framework of experiments, hypothesis testing, sources of bias in experiments, and how they relate specifically to A/B testing.
Learning Objectives
You will be able to:
- Explain the main reasons to conduct experiments.
- Understand the framework of conducting an experiment.
- Define key components of an experiment including the outcome, sources of variation, and the necessary data.
- Explain how experimental design relates to A/B tests.
- Define the key steps and terms in hypothesis testing.
Content
| Topic | About |
|---|---|
| Full Lesson Deck | Explain the terminology and framework of designing an experiment and the basics of hypothesis testing |
| 02 Hypothesis testing in action | See hypothesis testing in action with Python |
Prerequisites
- Write and run Python code in a Jupyter notebook.
- Create basic Python functions.
- Python programming skills including using modules and libraries.
- Use
pandas.
References
📖 Reference Materials
Important note
Please ignore the _layouts folder and the config.yml file in the root of this repo. They are needed to make sure the repo renders well; please don’t change them or delete them and your repo will work fine :)