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Hacker Stats in Python Part 1

Join us for this hands-on training where you will sharpen your skills in statistical inference by exploring multiple facets of a rich data set. You will perform exploratory data analysis, make informative graphics, compute confidence intervals, and perform hypothesis tests, all using a "hacker stats" approach with Python. The session runs for three hours, taking you from start to finish of a statistical analysis.

What will I learn?

You will learn how to:

  • Create effective visualizations of empirical distributions

  • Use random number generation as an engine for statistical inference ("hacker stats")

  • Compute confidence intervals of relevant summary statistics

What should I prepare?

Please note, a Gmail account is required in order to use Colaboratory, a free Jupyter notebook environment. You can join the webinar from your web browser following the instructions you receive in your registration email. All required data/resources will be provided in the training. You can also register now for Part 2.

Who should attend?

This course is open to all DataCamp Premium learners, looking to hone their skill in statistical inference. We recommend that you have taken the following course before attending:


Justin Bois Headshot
Justin Bois

Lecturer at the California Institute of Technology

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