In the previous two chapters, you learned about two very important concepts: mean (μ), which allows us to estimate a measurement from various observations, and standard deviation (σ), which allows us to measure the spread of our observations.

On its own, each concept is useful, but together, they are even more powerful: we can use them as parameters for the most famous probability distribution of all, the normal distribution.

In this chapter you’ll learn how to use the normal distribution to determine an exact probability for your degree of certainty about one estimate proving true compared to others. The true goal of ...

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