Answer:
<u><em>Part a:</em></u> Since the calculated value of t = 2.412 does not fall in the critical region t > ± 2.539 we conclude that population mean expense ratio does not exceed 1% at 0.01 significance level.
<u><em>Part b:</em></u> Yes we accepted the null hypothesis when it is false so we made a type II error.
<u><em>Part c:</em></u> Power = 0.6591=0.66
Step-by-step explanation:
<u><em>Part a:</em></u>
Let the null and alternate hypotheses be
H0: u ≤ 1 against the claim Ha: u > 1
The significance level is ∝=0.01
As the standard deviation of the population is not given we use t- test which has n-1= 20-1= 19 degrees of freedom
This is one tailed test the critical region is t > ± 2.539
The mean is calculated to be 1.24 and standard deviation of the sample = s= 0.4486
We take population mean = u= 1
The test statistic is
t = x`-u/ s/ √n
t= 1.24-1 / 0.445/√20
t= 0.24/0.0995
t= 2.412
Since the calculated value of t = 2.412 does not fall in the critical region t > ± 2.539 we conclude that population mean expense ratio does not exceed 1% at 0.01 significance level.
<u><em>Part b:</em></u>
Type I errors are those errors when the null hypothesis is true and is rejected.
Type II errors are those in which the null hypothesis is false and is accepted.
If we had rejected the null hypothesis as it was true then we would have made a type I error.
Population mean = u = 1.33
And our null hypothesis is u= 1
Yes we accepted the null hypothesis when it is false so we made a type II error.
<u><em>Part c:</em></u>
When σ= 0.5
For Part a: μ= 1.33
Power = P (reject H0/ H0 is false)
= 1-β
P (reject H0/ H0 is false) = P (z > 2.539+ (u`-u0) / σ*√n)
= P (z > 2.539+ (1-1.33) /0.5 *√20)
=P (z > 2.539-2.9516)
= P (z > 0.4126)
= 0.5 - P (z= 0.2938) from the area of table.
= 0.5- 0.1591
=0.3409
Power = 1-β = 1- 0.3409= 0.6591=0.66
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