Statistics is the science of analyzing data, and in this lesson, you'll learn the basics! Discuss statistical modeling and parameterizing models, too.
This statistics lesson covers the two most important point estimators: the sample average for the mean, and the population variance for the variance.
This lesson covers the idea of the p-value, which is a numerical way of characterizing the evidence against a particular hypothesis with a test statistic.
Confidence intervals contain all numbers between a and b, and can be calculated with the Central Limit Theorem, which is covered in this statistics lesson!
Bayesian statistics treats the parameters as if they are random variables. In this stats lesson, use Bayes' Rule to update the distribution of the parameters.
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