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Type I Error and Type II Error

A randomized trial comparing the efficacy of two drugs showed a difference between the two (with a P value < .05). Assume that in reality, however, the two drugs do not differ. This is therefore an example of a Type I error. Why is it NOT a Type II error? Is it because Type II error are defined as decision: conclude treatments are not different, but in type II errors the treatments are really different?

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RESPONSE:

Hi,

Let's take a closer look at these two interesting questions separately.

1. A randomized trial comparing the efficacy of two drugs showed a difference between the two (with a P value < .05). Assume that in reality, however, the two drugs do not differ. This is therefore an example of a Type I error.

By definition, it is a type one error: A type 1 error is rejecting the null hypothesis when it is true.

It often helps to set up the null and alternative hypothesis. For this experiment your null and alternative hypothesis would be:

Ho: ...

Solution Summary

Referring to a question where a randomized trial comparing the efficacy of two drugs that found a significant difference between the efficacy of the two drugs (with a P value < .05), when in reality there was no difference. This solution explains why this is an example of a Type I error and NOT a Type II error.

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