Spreadsheets Tutorial: How far from average?

Want to learn more? Take the full course at https://learn.datacamp.com/courses/introduction-to-statistics-in-spreadsheets at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Let's now learn how to measure a data point's distance from the average. The exercises following this video will explore US train ridership to understand how it varies over time. So jump aboard the stats train! Variance measures how dispersed a dataset is from its mean. The smaller the variance, the less spread the data is. Conversely, large differences between data points increase the variance. Column A repeats with no variation. Its variance is 0. In B, one value - 14 - is different yet close to the others. Its variance is 3. Column C has an outlier - 100. As a result, its variance is the highest among the three. To calculate variance, first calculate the mean. 10,14, 10 and 10 divided by 4 equals 11. Next, subtract the mean from each value. For the first, third, and fourth values, 10 minus 11 is -1. For the second value, 14 minus 11 leaves 3. Easy huh? In the 3rd step, square all these differences from the average. -1 squares to 1, and 3 squared equals 9. Finally, take another average of the squared differences, 1+9+1+1=12 divided by 4 equals 3. That was easy, but a bit cumbersome. Thankfully there is a formula to calculate variance. Simply call VARP with an array, as shown in this example in which I calculate the variance for all 3 columns. Next stop Standard Deviation! Keep in mind variance is the average of squared values. Thus the variance is different from the original sample values making it less intuitive! Most often you will need to make sense of the variation by putting it in the scale of the original data. This is done by taking the square root of the variance, called standard deviation. After taking the variance with VARP can use SQRT, squareroot, to calculate the standard deviation. More easily you can pass an