A Gentle Introduction to Estimation Statistics for Machine Learning

Last Updated on August 8, 2019

Statistical hypothesis tests can be used to indicate whether the difference between two samples is due to random chance, but cannot comment on the size of the difference.

A group of methods referred to as “new statistics” are seeing increased use instead of or in addition to p-values in order to quantify the magnitude of effects and the amount of uncertainty for estimated values. This group of statistical methods is referred to as “estimation statistics“.

In this tutorial, you will discover a gentle introduction to estimation statistics as an alternate or complement to statistical hypothesis testing.

After completing this tutorial, you will know:

• Effect size methods involve quantifying the association or difference between samples.
• Interval estimate methods involve quantifying the uncertainty around point estimations.
• Meta-analyses involve quantifying the magnitude of an effect across multiple similar independent studies.

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