Complete options are;
a. The approximation requires np > 10 and n(1 - p) > 10.
b. The sample size here is too small to use the Normal approximation to the binomial.
c. The approximation requires np > 30.
d. The Normal approximation works better if the success probability p is close to p = 0.5.
Answer:
Option C is false
Step-by-step explanation:
Looking at the options,
In normal approximation to the binomial,
n is the sample size,
p is the given probability.
q = 1 - p
Now, one of the conditions for using normal approximation to the binomial is that; np and nq or n(1 - p) must be greater than 10.
This means that option A is true because we require np or n(1 - p) to be greater than 10.
From Central limit theorem, the sample size needs to be more than 30 for us to use normal approximation. Our sample is 10. Thus, option B is true.
The approximation doesn't require np > 30. Rather it's the sample size that needs to be more than 30. Thus, option C is false.
Generally, when the value of p in a binomial is close to 0.5, the normal approximations will work better than when the value of p is closer to either 0 or 1. The reason is that: for p = 0.5, the binomial distribution will be symmetrical. Thus, option D is correct.
