![]() ![]() All of the other 18 shots are ignored when calculating ES. The example below shows muzzle velocities recorded over 20 shots, and we can see the ES is entirely dependent on the difference between shot #11 (the fastest) and #17 (the slowest). ![]() Adam MacDonald explains an important aspect when it comes to ES: “ For normally distributed sample data, the extreme spread is a misleading measure of the variation because it ignores the bulk of the data and focuses entirely on whether extreme events happened to occur in that sample.” (Not sure what “normally distributed” means? Read Part 1. In general, SD is usually a more reliable stat when it comes to quantifying the muzzle velocity variation. I’ll try to provide a balanced perspective on when we should use one or the other. There are scenarios where SD is the best to use, and other scenarios where ES may be more helpful. So it’s probably a bad idea to be completely dismissive of either ES or SD. So here is a very important point: An over-reliance on any descriptive statistic can lead to misleading conclusions.” – Charles Wheelan Descriptive statistics can be like online dating profiles: technically accurate and yet pretty darn misleading! Descriptive statistics exist to simplify, which always implies some loss of detail or nuance. The bad news is that any simplification invites abuse. “Descriptive statistics are very good at summing up a bunch of data points into a single number. But remember this important point from the last article, when it comes to any descriptive statistic, like ES or SD: ![]() Some shooters have strong opinions about which of those two measures are most applicable or relevant when it comes to long-range shooting, and they might completely ignore one or the other. (Note: Part 1 explained SD in detail, so please read that if you aren’t familiar with it – or the rest of this won’t make sense.) A low SD indicates all our velocities are closer to the average, while a high SD indicates the velocities are spread out over a wider range.
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