# HR 101-Statistics

It’s Seiden folks. ‘Nuff said.

If you were teaching a ‘Finance Basics for HR’ course, what type of information would you share? Statistics: the most important class most people blow off. Right out of the gate, we need to establish two things: first, math is not hard. Your whole, “I’m not good at math” thing is an illusion.

Second, even with stats, you cannot predict the future. The language of statistics is, “this is likely to happen,” or “this group will probably like it.” That can be frustrating in a world where people want you to answer questions with clipped absolutes such as “Definitely” and “For sure.” Once you accept that you actually use math every day and are good at it, and make peace with a world where things are “likely” and not “certain,” you’re halfway home. To get the rest of the way, dive into these topics: how to get accurate information about an organization (or event) without having to survey everyone; how to create feedback forms that mean something; how to measure training’s impact on the bottom line using actual performance data… and while we’re at it, how to measure the impact of hiring practices, leadership styles, pay rates, and reward systems, too. That’s probably a good start. What’s critical to know? There are a few statistics concepts that are incredibly, incredibly useful. Here are four worth knowing right now:

1. Regression to the mean. Simply put: whatever’s happening today, the trend will eventually stall and head the opposite direction… all by itself. You can nudge average performance up (or down), but you can’t suddenly make everyone superstars. (If you do, expect the crash.) An important implication of this is that when employees are split into “high potential” and “needs development” cohorts, and then provided training specific to those groups, you are likely to be disappointed in the “high potential” training and overly pleased with the “needs development” training, because of a natural tendency for these groups’ performance to gravitate toward average. This change will happen independent of the training you provide, and you need to ask yourself, “Did my training program provide additional benefit beyond what would have happened normally?”
2. Margin of error. A measure of how “real” is your information. What’s the difference between a “4.2” and a “4.8” on a 360° survey? Knowing the survey’s margin of error will tell you if there is a difference at all… or if statistically, those numbers are the same. Thinking that differences are meaningful when they are not is a common mistake, and one I see frequently in HR in the analysis of 360° data.