Answer:
(1) The probability that the sample percentage indicating global warming is having a significant impact on the environment will be between 64% and 69% is 0.3674.
(2) The two population percentages that will contain the sample percentage with probability 90% are 0.57 and 0.73.
(3) The two population percentages that will contain the sample percentage with probability 95% are 0.55 and 0.75.
Step-by-step explanation:
Let X = number of senior professionals who thought that global warming is having a significant impact on the environment.
The random variable X follows a Binomial distribution with parameters n = 100 and p = 0.65.
But the sample selected is too large and the probability of success is close to 0.50.
So a Normal approximation to binomial can be applied to approximate the distribution of p if the following conditions are satisfied:
- np ≥ 10
- n(1 - p) ≥ 10
Check the conditions as follows:
![np= 100* 0.65=65>10\\n(1-p)=100* (1-0.65)=35>10](https://img.qammunity.org/2021/formulas/mathematics/college/34cb4i1zkgcknzlb49c84g7p2b90c7r8r1.png)
Thus, a Normal approximation to binomial can be applied.
So,
.
(1)
Compute the value of
as follows:
![P(0.64<\hat p<0.69)=P((0.64-0.65)/(√(0.002275))<\frac{\hat p-p}{\sqrt{(p(1-p))/(n)}}<(0.69-0.65)/(√(0.002275)))](https://img.qammunity.org/2021/formulas/mathematics/college/8z2orkrn2lvof0ffd01wgkahzpjm7xbt5y.png)
![=P(-0.20<Z<0.80)\\=P(Z<0.80)-P(Z<-0.20)\\=0.78814-0.42074\\=0.3674](https://img.qammunity.org/2021/formulas/mathematics/college/s4imqvldpoui5j7s7v504uu5r6xosa2a2m.png)
Thus, the probability that the sample percentage indicating global warming is having a significant impact on the environment will be between 64% and 69% is 0.3674.
(2)
Let
and
be the two population percentages that will contain the sample percentage with probability 90%.
That is,
![P(p_(1)<\hat p<p_(2))=0.90](https://img.qammunity.org/2021/formulas/mathematics/college/vkm8oelj497qcb21ugh8fn0yfmfrg1az9q.png)
Then,
![P(p_(1)<\hat p<p_(2))=0.90](https://img.qammunity.org/2021/formulas/mathematics/college/vkm8oelj497qcb21ugh8fn0yfmfrg1az9q.png)
![P(\frac{p_(1)-p}{\sqrt{(p(1-p))/(n)}}<\frac{\hat p-p}{\sqrt{(p(1-p))/(n)}}<\frac{p_(2)-p}{\sqrt{(p(1-p))/(n)}})=0.90](https://img.qammunity.org/2021/formulas/mathematics/college/lfdpf9jhnii44f4x1uhzkje2gb320hq266.png)
![P(-z<Z<z)=0.90\\P(Z<z)-[1-P(Z<z)]=0.90\\2P(Z<z)-1=0.90\\2P(Z<z)=1.90\\P(Z<z)=0.95](https://img.qammunity.org/2021/formulas/mathematics/college/7j06s6am0g2l41l1vic0pq3s6t5qotocun.png)
The value of z for P (Z < z) = 0.95 is
z = 1.65.
Compute the value of
and
as follows:
![z=\frac{p_(2)-p}{\sqrt{(p(1-p))/(n)}}\\1.65=\frac{p_(2)-0.65}{\sqrt{(0.65(1-0.65))/(100)}}\\p_(2)=0.65+(1.65* 0.05)\\p_(1)=0.7325\\p_(1)\approx0.73](https://img.qammunity.org/2021/formulas/mathematics/college/ujb5egivdx7f36rxsymfoyf22qxgecwz6v.png)
Thus, the two population percentages that will contain the sample percentage with probability 90% are 0.57 and 0.73.
(3)
Let
and
be the two population percentages that will contain the sample percentage with probability 95%.
That is,
![P(p_(1)<\hat p<p_(2))=0.95](https://img.qammunity.org/2021/formulas/mathematics/college/zy1wlyc6oscjvu1dqzgtf6bxhi14sfxai7.png)
Then,
![P(p_(1)<\hat p<p_(2))=0.95](https://img.qammunity.org/2021/formulas/mathematics/college/zy1wlyc6oscjvu1dqzgtf6bxhi14sfxai7.png)
![P(\frac{p_(1)-p}{\sqrt{(p(1-p))/(n)}}<\frac{\hat p-p}{\sqrt{(p(1-p))/(n)}}<\frac{p_(2)-p}{\sqrt{(p(1-p))/(n)}})=0.95](https://img.qammunity.org/2021/formulas/mathematics/college/mrtbbmagf35b4hisdhu6ajmvaci6v0krg9.png)
![P(-z<Z<z)=0.95\\P(Z<z)-[1-P(Z<z)]=0.95\\2P(Z<z)-1=0.95\\2P(Z<z)=1.95\\P(Z<z)=0.975](https://img.qammunity.org/2021/formulas/mathematics/college/kobehq2c9e491gkrvqtteqkd6titwd4yid.png)
The value of z for P (Z < z) = 0.975 is
z = 1.96.
Compute the value of
and
as follows:
![z=\frac{p_(2)-p}{\sqrt{(p(1-p))/(n)}}\\1.96=\frac{p_(2)-0.65}{\sqrt{(0.65(1-0.65))/(100)}}\\p_(2)=0.65+(1.96* 0.05)\\p_(1)=0.748\\p_(1)\approx0.75](https://img.qammunity.org/2021/formulas/mathematics/college/no3k246ekc9f3vmat3mw4kei0aob402mad.png)
Thus, the two population percentages that will contain the sample percentage with probability 95% are 0.55 and 0.75.