# A Guide to Metrics in Exploratory Data Analysis | by Esmaeil Alizadeh | Dec, 2020

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Estimates of location are measures of the central tendency of the knowledge (the place many of the information is positioned). In statistics, that is typically referred to as the primary second of a distribution.

## Mean

The mathematics imply, or just imply or moderate is one of the crucial well-liked estimate of location. There other variants of imply, corresponding to weighted imply or trimmed/truncated imply. You can see how they may be able to be computed beneath.

the place n denotes the whole collection of observations (rows).

Weighted imply (equation 1.2) is a variant of imply that can be utilized in eventualities the place the pattern information does no longer constitute other teams in a dataset. By assigning a bigger weight to teams which might be under-represented, the computed weighted imply will extra as it should be constitute all teams in our dataset.

Extreme values can simply affect each the imply and weighted imply since neither one is a sturdy metric!

Another variant of imply is the trimmed imply (eq. 1.3) that may be a powerful estimate.

Robust estimate: A metric that isn’t delicate to excessive values (outliers).

The trimmed imply is used in calculating the general ranking in many sports activities the place a panel of judges will each and every give a ranking. Then the bottom and the very best rankings are dropped and the imply of the rest rankings are computed as part of the general ranking[2]. One such instance is in the global diving ranking device.

In statistics, refers to a pattern imply, while μ refers to the inhabitants imply.

## A Use Case for the Weighted Mean

If you wish to have to purchase a smartphone or a smartwatch or any device the place there are lots of choices, you’ll use the next manner to make a selection amongst quite a lot of choices to be had for a device.

Let’s suppose you wish to have to purchase a smartphone, and the next options are necessary to you: 1) battery lifestyles, 2) digicam high quality, 3) value and four) the telephone design. Then, you give the next weights to each and every one:

Let’s say you’ve got two choices an iPhone and Google’s Pixel. You may give each and every function a ranking of a few worth between 1 and 10 (1 being the worst and 10 being the most productive). After going over some evaluations, you can provide the next rankings to the options of each and every telephone.

So, which telephone is best for you?

iPhone ranking​=0.15×6+0.3×9+0.25×1+0.3×9=6.55