Well, 1 ft = .333333 yards
So, do .333333 x 72 to get your answer.
You should get 23.999976
So, now just round it and you should get 24 as your final answer.
Thanks for the free points
Part a)
It was given that 3% of patients gained weight as a side effect.
This means


The mean is


The standard deviation is



We want to find the probability that exactly 24 patients will gain weight as side effect.
P(X=24)
We apply the Continuity Correction Factor(CCF)
P(24-0.5<X<24+0.5)=P(23.5<X<24.5)
We convert to z-scores.

Part b) We want to find the probability that 24 or fewer patients will gain weight as a side effect.
P(X≤24)
We apply the continuity correction factor to get;
P(X<24+0.5)=P(X<24.5)
We convert to z-scores to get:

Part c)
We want to find the probability that
11 or more patients will gain weight as a side effect.
P(X≥11)
Apply correction factor to get:
P(X>11-0.5)=P(X>10.5)
We convert to z-scores:


Part d)
We want to find the probability that:
between 24 and 28, inclusive, will gain weight as a side effect.
P(24≤X≤28)=
P(23.5≤X≤28.5)
Convert to z-scores:
