Respuesta :
Answer:
a. The test statistic is 2 and we conclude that the new ad campaign is not signficantly better.
Step-by-step explanation:
They used to be able to sell to 50% of those who saw their ads. Test if the new campaign is better.
At the null hypothesis, we test is it is the same, that is, the proportion is the same.
[tex]H_0: p = 0.5[/tex]
At the alternate hypothesis, we test if it is significantly better, that is, the proportion is above 50%.
[tex]H_1: p > 0.5[/tex]
The test statistic is:
[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
In which X is the sample mean, [tex]\mu[/tex] is the value tested at the null hypothesis, [tex]\sigma[/tex] is the standard deviation and n is the size of the sample.
0.5 is tested at the null hypothesis:
This means that [tex]\mu = 0.5, \sigma = \sqrt{0.5*0.5} = 0.5[/tex]
They take a random sample of 100 potential buyers and find that they convinced 60 of these people to buy their product.
This means that [tex]n = 100, X = \frac{60}{100} = 0.6[/tex]
Test statistic:
[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{0.6 - 0.5}{\frac{0.5}{\sqrt{100}}}[/tex]
[tex]z = 2[/tex]
The test statistic is 2.
P-value of the test and decision:
The p-value of the test is the probability of finding a sample proportion above 0.6, which is 1 subtracted the by p-value of z = 2.
Looking at the z-table, z = 2 has a p-value of 0.9772.
1 - 0.9772 = 0.0228.
The p-value of the test is 0.0228 > 0.01, which means that we cannot conclude that the new ad campaign is signficantly better, so the correct answer is given by option A.
