Course · Interview foundations
Statistics for Data Engineers
Free statistics course for data science and analysis: averages and spread, distributions, the central limit theorem, hypothesis tests and A/B testing.
- Lessons
- 4
- Interview questions
- 0
- Projects & case studies
- 0
- Reading time
- ~1 h
Your progress
Saved in this browser onlyCourse structure
- 1 lessonStart hereThe complete overview of the course in one read.
- 1 lessonBeginnerCore concepts you will use every day.
- 2 lessonsIntermediatePatterns used in production pipelines.
Practise
Lessons
Work through the lessons in order. Completed lessons show a tick; lessons you have opened are outlined.
Start here
The complete overview of the course in one read.
Beginner
Core concepts you will use every day.
Intermediate
Patterns used in production pipelines.
- Hypothesis Testing and P-Values Explained SimplyHypothesis testing in plain words: null hypotheses, p-values, t-tests, a permutation test that shows what a p-value means, and confidence intervals, in Python.
- A/B Testing: Design, Sample Size and AnalysisHow to run an A/B test properly: pick a metric, calculate the sample size, analyse conversions with a z-test and confidence interval, and avoid common pitfalls.
Resources
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