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Rejecting a true null hypothesis.

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10y ago

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Relationship between type 1 error and type 2 error?

In statistics, there are two types of errors for hypothesis tests: Type 1 error and Type 2 error. Type 1 error is when the null hypothesis is rejected, but actually true. It is often called alpha. An example of Type 1 error would be a "false positive" for a disease. Type 2 error is when the null hypothesis is not rejected, but actually false. It is often called beta. An example of Type 2 error would be a "false negative" for a disease. Type 1 error and Type 2 error have an inverse relationship. The larger the Type 1 error is, the smaller the Type 2 error is. The smaller the Type 2 error is, the larger the Type 2 error is. Type 1 error and Type 2 error both can be reduced if the sample size is increased.


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Type your answer here omission error commission error principles error compensatory error


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type1 error is more dangerous


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What happens to the confidence interval if you increase the margin of error?

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In hypothesis testing, a Type I error occurs when a true null hypothesis is incorrectly rejected, while a Type II error occurs when a false null hypothesis is not rejected.


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