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Confidence Intervals vs Hypothesis Tests
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There are so many similarities between Confidence Intervals and Hypothesis Tests, that it is easy to confuse the two. In this video, I explain the similarities and differences between them.
In short, they both rely on intervals to help us see whether a sample is consistent with a particular hypothesis. A Confidence Interval constructs its interval around a sample mean, and checks whether a hypothesized population parameter lies within this acceptable range.
A Hypothesis Test, on the other hand, constructs an interval around a hypothesized population parameter, and checks whether a sample mean lies within this acceptable range.
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In short, they both rely on intervals to help us see whether a sample is consistent with a particular hypothesis. A Confidence Interval constructs its interval around a sample mean, and checks whether a hypothesized population parameter lies within this acceptable range.
A Hypothesis Test, on the other hand, constructs an interval around a hypothesized population parameter, and checks whether a sample mean lies within this acceptable range.
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