Surveys and polls are incredibly powerful tools. They can help us understand what people are thinking and sometimes even why. They can help us predict the ways in which people will react to events and announcements. They can inform decisions that must be made by governments, companies, and individuals. But for all of their powers, polls and surveys are only as effective as are the people who read and interpret them. In order to make sense of raw data and even processed and presented results, we need to understand statistics and the principles that it comprises. Among the most important statistical concepts that we should familiarize ourselves with is standard deviation.
Standard deviation is a measure of how spread out the data in a set is. In other words, a standard deviation tells us whether the responses or results from a poll, survey or another type of study are grouped together or spread wide apart.
For example, if you were to measure the heights of a group of children in a kindergarten class, you could calculate a standard deviation for that data set. Then, if you were to repeat your measurements but were to include students from every grade, from kindergarteners to seniors in high school, then you could calculate a new standard deviation.
You’d expect the second standard deviation to be larger because the heights would vary across a wider range since the older kids would be much taller than anyone in our original kindergarteners-only set.
Standard deviation is one of the most valuable concepts in statistics. It can be used to better understand data, and it can be used to determine whether or not particular data points are useful or relevant.
Let’s take those one at a time. Knowing the standard deviation matters for interpretation in ways that are easy to understand. Imagine we determined an average—or “mean”— height for our kindergarteners and decided to use that information to build coat cubbies. We’d be glad to hear that the standard deviation is small.
Our average is pretty reflective of most kindergarteners, so we can build the cubbies at that height. Meanwhile, the standard deviation from our larger study would be large, warning us that we should not assume that building coat cubbies at the average height of a K-12 student is a good idea. It would be too tall for kindergarteners and too short for seniors.
Standard deviation can also be used to determine outliers or data points that are far from the clump of other responses. For instance, imagine that our school had a 7’7” future NBA star. Including that height in our averages would skew our results, making us imagine that our typical students are taller than they actually are. What we should do is recognize this data point as an outlier, and not let it lead to us building enormous coat cubbies.
Statistics are powerful things but only when they’re well understood. Polls and surveys that are done by reputable organizations and services account for things like outliers and provide information about standard deviation.
When you analyze quality poll and survey results, whether you’re making a decision for your company or simply reading the news ahead of a big election, do your best to read the information properly and interpret it wisely. Don’t make conclusions that aren’t supported by the data.
If you are interested in even more business-related articles and information from us here at Bit Rebels then we have a lot to choose from.
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