Data Science & AIStatisticsIntermediate
Statistics for Data Science
The inference you need before you trust any experiment result.
4.7(389 ratings) 46 lessons · 7 modules 15h2.1k students
SK
What you'll learn
- Interpret confidence intervals without misusing them
- Design experiments with adequate statistical power
- Avoid p-hacking and the multiple-comparisons trap
- Decide when a result is real and when it is noise
About this course
Most bad data decisions are statistical, not technical. This course covers distributions, confidence intervals, hypothesis testing, power analysis and the multiple-comparisons trap, with every concept tied to an A/B test decision.
Curriculum
7 modules · 46 lessons · 15h
The detailed curriculum for this course is being finalised. The outline covers 46 lessons across 7 modules.
Requirements
- High-school algebra
- Some familiarity with spreadsheets
Who this course is for
- Analysts and data scientists
- Product managers running experiments
Student reviews
No written reviews yet. The course has 389 ratings with an average of 4.7 out of 5.
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