From the course: Complete Guide to Excel Statistics with Copilot
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The central limit theorem
From the course: Complete Guide to Excel Statistics with Copilot
The central limit theorem
- [Instructor] The central limit theorem, it's a rather simple concept that is sort of intuitive, but with some interesting and helpful twists. We've already started to discover that when we take a sample, the larger our sample size, the more confident we are in our sample. Confident about what? Confident that this one sample reflects the entire population. But the central limit theorem takes this a bit further. The central limit theorem goes on to tell us that the more samples we take, the closer the average of our sample means will get to the actual population mean. So, if we take one sample with a reasonable sample size, we have some evidence. If we take lots of samples, the evidence starts to point us closer and closer to the truth. But the central limit theorem actually tells us a bit more. It says that as we start to take many more samples, dozens of samples, hundreds of samples, even thousands of samples, the sample means, if we plotted them as a histogram, they would begin to…
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