Answer:
The probability is 0.10.
Step-by-step explanation:
Hello!
When conducting a test there are four different decisions you can make.
1. Reject the null hypothesis when the hypothesis is false (This is a correct decision) (True positive, TP)
2. Reject the null hypothesis when the hypothesis is true (This decision is also known as Type I error) (False positive, FP)
3. Fail to reject the null hypothesis when the hypothesis is true (This is a correct decision) (True negative, TN)
4. Fail to reject the null hypothesis when the hypothesis is false (This decision is also known as Type II error) (False negative, FN)
Each of these decisions has an associated probability:
1. P(TP)= 1-β (Known as the power of the test)
2. P(FP)= α (Known as significance level)
3. P(TN)= 1-α
4. P(FN)= β
With this in mind, if the tested null hypothesis is "The new equipment has no effect in the jewelry making production" vs the alternative hypothesis "The new equipment increases the jewelry making production" and Frances rejects the null Hypothesis when this is in fact, true, then the decision made is a Type I error and its probability is α= 0.10
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