Statistical Moments in Data Science interviews | Statistics - Medium

The article is organized into two parts:
I. Math Refresher
II. Questions from data science interviews related to the topic

Essential math for Data Scientists explained from scratch, writes Agnieszka Kujawska, PhD, published in Towards Data Science.

Moments are set of statistical parameters used to describe a distribution. The calculations are simple, so are often used as a first quantitative insight into the data. A good understanding of data should always be the step before training any advanced ML model. It allows minimizing the time required to choose the methodology and interpret results.

In physics, moments refer to mass and inform us how the physical quantity is located or arranged. In math, moments refer to something similar — the probability distribution — a function that explains how probable are different possible outcomes of an experiment. To be able to compare different data sets we can describe them using the first four statistical moments:
1. The expected value
2. Variance
3. Skewness
4. Kurtosis

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