Type I error: A company that manufactures steel wires guarantees that the mean breaking strength (in kilonewtons) of the wires is greater than 50 . They measure the strengths for a sample of wires and test $H_{0}: \mu=50$ versus $H_{1}: \mu> 50$.
Part 1 of 3
If a Type I error is made, what conclusion will be drawn regarding the mean breaking strength?
The conclusion will be that the mean breaking strength is greater than 50.
Part: $1 / 3$
Part 2 of 3
If a Type II error is made, what conclusion will be drawn regarding the mean breaking strength?
The conclusion will be that the mean breaking strength is (Choose one) $\mathbf{\nabla} 50$.
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Step 1 ：A Type I error occurs when the null hypothesis (H0) is true, but is rejected. It is asserting something that is absent, a false hit. A Type I error is often considered the more serious error in the two and is often more controlled.

Step 2 ：A Type II error occurs when the null hypothesis is false, but erroneously fails to be rejected. It is failing to assert what is present, a miss.

Step 3 ：In this case, the null hypothesis (H0) is that the mean breaking strength of the wires is 50, and the alternative hypothesis (H1) is that the mean breaking strength is greater than 50.

Step 4 ：If a Type I error is made, the conclusion will be that the mean breaking strength is greater than 50, when in reality it is not. This is a false positive.

Step 5 ：If a Type II error is made, the conclusion will be that the mean breaking strength is not greater than 50, when in reality it is. This is a false negative.