edX
edXStatistics, Confidence Intervals and Hypothesis Tests
308 studentsINTERMEDIATEEnglish
Korshub's take
From Probability to Statistical Inference
Statistical thinking is the bridge from data to decisions. This course builds your foundation systematically: from probability distributions and the Central Limit Theorem through confidence intervals and hypothesis testing.
You'll learn to estimate unknown parameters, construct confidence intervals that capture the uncertainty in your estimates, and test hypotheses rigorously—understanding the errors that can occur and how to manage them.
Essential for anyone working with data: researchers, analysts, engineers, and data scientists who need to make claims backed by evidence and understand the limits of what data can tell us.
About this course
Review a library of discrete and continuous probability distributions. ,Meet the normal distribution and the Central Limit Theorem, and discover how they are applied in practice. ,Recognize elementary methods of descriptive statistics. ,Study methods that can be used to estimate the unknown parameters of a distribution. ,Learn what confidence intervals are, how they are used, and how to formulate and interpret confidence intervals for a variety of probability distributions and their parameters. ,Learn what hypothesis tests are, how they are used, and the types of errors that can occur with hypothesis testing. ,Formulate and interpret hypothesis tests for a variety of probability distributions and their parameters.
Price
$498
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