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In this course, you will learn:
- Statistical inference's logical and conceptual frameworks
- How to do A/B testing, permutation testing, and hypothesis testing
- The purpose and effectiveness of resampling techniques
- P-values, quantifying uncertainty, and producing confidence intervals using the bootstrap method are all examples of relationships between sample size and accuracy.
- How should the findings of hypothesis testing be interpreted?
