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Inferential Statistics

This section covers hypothesis testing, confidence intervals, and regression analysis.

Topics Covered

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Prerequisites

Descriptive statistics and probability knowledge

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Tutorial

Apr 11, 202611 min read

Central Limit Theorem

When you sample validation scores across multiple CV folds or user cohorts, your underlying data may be heavily skewed or non-normal. Yet, as sample size grows,…

Tutorial

Apr 11, 202611 min read

Estimates and Estimators

You want to know a model's true generalization accuracy — its expected performance on all possible test inputs. You cannot observe this directly. You have six C…

Tutorial

Apr 11, 20269 min read

Hypothesis Testing

A model achieves 83.8% mean CV accuracy. The current baseline is 80%. Is 83.8% genuinely better, or is that 3.8-percentage-point gap noise from six folds? You c…

Tutorial

Apr 11, 202611 min read

P-Value

When you launch a new feature and see a 2% lift in conversion, your immediate question is whether the gain is real or a fluke of sample noise. A $p$-value quant…

Tutorial

Apr 11, 202610 min read

Z-Test

Historical benchmarks show the baseline model achieves 80% accuracy with known σ=0.05 (computed from millions of CV runs). Your new model achieves x̄=0.838 acro…