In each of the following cases state whether or not the normal approximation to the binomial should be used for a significance test on the population proportion p.

An = 10 and H0: p = 0.4.

Bn = 100 and H0: p = 0.6.

Cn = 1000 and H0: p = 0.996.

Dn = 500 and H0: p = 0.3.

The normal approximation to a binomial can be used for a significance test on the population proportion p if np > 15.

a. n = 10 and H0: p = 0.4. => np = 10(0.4) = 4 [can not be used]

Bn = 100 and H0: p = 0.6. => np = 100(0.6) = 60 [can be used]

Cn = 1000 and H0: p = 0.996. => np = 1000(0.996) = 996 [can be used]

Dn = 500 and H0: p = 0.3. => np = 500(0.3) = 150 [can be used0

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In each of the following cases state whether or not the normal approximation to the binomial should be used for a significance test on the population proportion p. An = 10 and H0: p = 0.4. Bn = 100 and H0: p = 0.6. Cn = 1000 and H0: p = 0.996. Dn = 500 and H0: p = 0.3.

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In each of the following cases state whether or not the normal approximation to the binomial should be used for a significance test on the population proportion p.

An = 10 and H0: p = 0.4.

Bn = 100 and H0: p = 0.6.

Cn = 1000 and H0: p = 0.996.

Dn = 500 and H0: p = 0.3.