A DataCamp course bridging coding and analysis. Over four hands-on chapters you compute summary statistics, reason about probability and common distributions, and learn the basics of correlation and experimental design — all in Python. Practical and applied, best for people who know some Python and want to add statistical thinking.
Good for: Adding practical statistics to your Python data skills.
Less suitable if: You do not know basic Python, or want deep statistical theory.
Requirements: Basic Python; some maths comfort helps.
Realistic time: Around 4 hours.
About this course
Introduction to Statistics in Python bridges coding and analysis. Over four hands-on chapters you compute summary statistics, reason about probability and common distributions, and learn the basics of correlation and experimental design — all in Python so the maths stays practical.
What you'll learn
Calculate and interpret summary statistics
Reason about probability and distributions
Measure correlation between variables
Understand the basics of experimental design
Apply statistical thinking in Python
Draw valid conclusions from sample data
This course includes
4h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
DataCamp runs on a subscription — roughly $14/month billed annually (more month-to-month), with the first chapter of each course free to try. A certificate of completion is included with the subscription.
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