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Continuous: Z-score tables

Continuous: Z-score tables

- [Narrator] What do we know so far? We know normal distribution is a continuous distribution. Typically it's illustrated via the normal curve. We also know that Z-scores provide a relative distance from the mean. A data point with a Z-score of 2.0 is two standard deviations above the mean. We've also learned about the power of the empirical rule and we learned how to calculate Z-scores for individual data points in our data sets. Those Z-scores can tell us how far that data point is from the mean, but Z-scores also allow us to calculate probabilities in a continuous distribution. For example, we know 68% of data points are within one standard deviation of the mean, which tells us that 32% of data points are outside of that area. Because the normal curve is symmetrical, we know 16% of those data points are more than one standard deviation from the mean in the positive direction, and 16% are more than one standard deviation from the mean in the negative direction. In order to find…

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