Step-by-step explanation:
1.
the expected sample mean is always the general mean : 168.5 pounds.
2.
the SD of a sample is the general SD / sqrt(sample size).
in our case
the sample SD = 68/sqrt(150) = 5.55217675...
3.
if we are looking for only the probability that any single woman is below 160 pounds, we would use the normal z calculation :
z = (x - mean)/SD = (160 - 168.5)/68 = -8.5/68
but we have here the question about the probability of the mean value of a whole sample of 150 women.
so, we need to adapt the z-calculation by the principle of 2) for the SD of a sample :
z = (x - mean)/(SD × sqrt(sample size)) =
= (160 - 168.5)/(68 × sqrt(150)) = -8.5/(68×sqrt(150)) =
= -0.010206207 ≈ -0.01
that gives us in the z-table the p-value 0.49601
this 0.49601 is the probability that a sample of 150 women has a mean value of below 160 pounds.
4.
similar to 3.
the z value we are looking for
z = (175 - 168.5)/(68 × sqrt(150)) = 6.5/(68 × sqrt(150)) =
= 0.007804747... ≈ 0.01
that gives us the p-value 0.50399.
that would be the probability of a sample mean of 175 or below.
to get above 175 we need to get the other side of the bell-curve :
1 - 0.50399 = 0.49601
so, this case has about the same probability as 3.
5.
as 3), just with the sqrt(200) instead of the sqrt(150).
z = -8.5/(68 × sqrt(200)) = -0.008838835... ≈ 0.01
so, the probability is still about the same as in 3) :
0.49601
6.
as 4) just with sqrt(200).
z = 6.5/(68 × sqrt(200)) = 0.006759109... ≈ 0.01
so, the probability is still about the same as for 4) :
0.49601
