![]() Example: Variability in normal distributionsYou are investigating the amounts of time spent on phones daily by different groups of people. Both of them together give you a complete picture of your data. If you know only the central tendency or the variability, you can’t say anything about the other aspect. High variability means that the values are less consistent, so it’s harder to make predictions.ĭata sets can have the same central tendency but different levels of variability or vice versa. Low variability is ideal because it means that you can better predict information about the population based on sample data. This is important because the amount of variability determines how well you can generalize results from the sample to your population. ![]() While the central tendency, or average, tells you where most of your points lie, variability summarizes how far apart they are. Frequently asked questions about variability. ![]()
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