Answer:
There is not a convincing statistical evidence, at the significance level of a = 0.05, that the manager's belief is correct.
As the null hypothesis maybe false accepting it makes a type II error.
Step-by-step explanation:
Let the null and alternate hypotheses be
H0: p ≤ 0.4 vs Ha : p>0.4
q= 1-p= 1-0.4= 0.6
The significance level alpha is 0.05
The critical region for one tailed test is Z> ± 1.645
The sample proportion is p^= x/n= 38/90=0.42222
Using the z statistic
z= p^- p/ √pq
z= 0.422-0.4/ √0.4*0.6
z= 0.04536
Since the calculated value of z= 0.04536 does not lie in the critical region Z> ± 1.645 we fail to reject null hypothesis.
There is not sufficient evidence to support the manager's claim.
Type I error is when we reject the true null hypothesis .
Type II error is when we accept the false null hypothesis .
As the null hypothesis maybe false accepting it makes a type II error.
Answer:
true
Step-by-step explanation:
Answer:
Step-by-step explanation:
Did you mean log (17*3)? If so, your log (17x3) becomes log 17 + log 3.
Did you mean log 17^3? If so, log 17^3 = 3 log 17.
Did you mean log 17*x*3? If so, this equals log 17 + log x + log 3
Step-by-step explanation:
let worth be y and age be x
y = k/x, where k is a constant, k ≠ 0
7000 = k/3
21000 = k
y = 21000/7
y = 3000
$3000
Topic: Direct and inverse proportions
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