Hypothesis testing allows us to test an idea. This is when we formulate two hypothesis and want to assess whether one of them can be rejected at a given level of certainty. While testing for the mean, the variance of the population can be either known or unknown. In real-life, it is far more common to not know the population variance. That’s why we use Student’s T-distribution more often.
Hypothesis testing is one of the most useful tools for statisticians and data scientists. Whenever we have to test an idea, it comes down to executing a hypothesis test.
Other related topics you might be interested to explore are Confidence Intervals, and Testing for the Mean with known variance.
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Hypothesis testing for the mean is among the topics included in the Quantitative Methods module of the CFA Level 1 Curriculum.