In Hypothesis Testing:
a Type I Error is committed when one fails to accept a true Null Hypothesis;
a Type II Error is committed when one fails to reject a false Null Hypothesis.
Here:
population mean is μ = 135;
sample size is n = 59;
significance level is α = 0.05;
sample standard deviation is s = 10;
and sample mean is Xbar = 140.
Construct (Xbar − μ)/[s/n0.5] as (140 − 135)/[10/590.5]
which reduces to 0.5[590.5] or 3.840572874.
For significance level of α = 0.05, with a right-tailed test,
one takes a critical value of z (or zc) equal to 1.645.
3.840572874 falls well past 1.645 into the right-hand region of rejection.
For
H0: μ ≤ 135 &
H1: μ > 135,
one then fails to accept H0 and concludes that μ exceeds 135.
The area to the right of 3.840572874 under the standard normal curve is given by
β equal to 1 − (0.5 + 0.4999386262) or 6.13737711 × 10-5.
The power of the test here is given by 1 minus the probability of failure to reject a false Null Hypothesis or 1 − Pr(Type II Error).
The power of a test is a measure of the test's efficiency in recognizing true hypotheses as valid and false hypotheses as flawed and here amounts to 1 − β or 1 − 6.13737711 × 10-5 or 0.9999386262 equivalent to 0.99, which corresponds to Choice A.