In: Statistics and Probability
Suppose a new production method will be implemented if a hypothesis test supports the conclusion that the new method reduces the mean operating cost per hour.
a. State the appropriate null and alternative hypotheses if the mean cost for the current production method is per hour.
h0: u [fill in the blank] 230
ha: u [fill in the blank] 230
b. What is the Type I error in this situation? What are the consequences of making this error?
Claiming u [fill in the blank] 230 when the new method [fill in the blank- does or does not] lower costs. A mistake could be implementing the method when it [fill in the blank- does or does not] help.
c. What is the Type II error in this situation? What are the consequences of making this error?
Claiming u [fill in the blank] 230 when the new method [fill in the blank-does or does not] lower costs. This could lead to not implementing a method that [fill in the blank-does or does not] lower costs.
a)
h0: u ≥ 230
ha: u < 230
b) In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a "false positive" finding), while a type II error is failing to reject a false null hypothesis (also known as a "false negative" finding).
Claiming u [less than] 230 when the new method [does not] lower costs. A mistake could be implementing the method when it [does not]help.
c) Claiming u [greater tna] 230 when the new method [does ] lower costs. This could lead to not implementing a method that [does] lower costs.