From the course: CompTIA Data+ (DA0-002) Cert Prep

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Variance and standard deviation

Variance and standard deviation

- [Instructor] The last two measures of dispersion that we need to discuss are variance and standard deviation. These values are related to each other, and they give us a sense of how values are spread from the mean. Let's start with variance. The variance is the average of the squared differences of each value in a dataset from the mean. We calculate variance with this formula. Now, once again, we have some Greek letters here, so I'm going to walk you through this formula. We saw a mu earlier in the course, that's the mean value for the population. And lowercase x is each of the values in the dataset. So we take each value in the dataset and subtract the mean from it. Then we square that difference. After calculating all the squared differences, we add them together and divide by N the number of values in the population. That gives us lowercase sigma squared, the variance. Now, with that explanation under our belts, let's try calculating the variance for our class height dataset. We…

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