Answer:
Ha: μ < 24
The test statistic is z = -1.75.
The pvalue of the test is 0.0401 > 0.02, which means that we do not reject the null hypothesis, as there is insufficient evidence.
Step-by-step explanation:
A recent survey reported that small businesses spend 24 hours a week marketing their business.
This means that the null hypothesis is:
[tex]H_0: \mu = 24[/tex]
A local chamber of commerce claims that small businesses in their area are not growing because these businesses are spending less than 24 hours a week on marketing.
This means that the alternate hypothesis is:
[tex]H_a: \mu < 24[/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.
24 is tested at the null hypothesis:
This means that [tex]\mu = 24[/tex]
The chamber conducts a survey of 93 small businesses within their state and finds that the average amount of time spent on marketing is 23.0 hours a week.
This means that [tex]n = 93, X = 23[/tex]
The population standard deviation is 5.5 hours
This means that [tex]\sigma = 5.5[/tex]
Value of the test-statistic:
[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{23 - 24}{\frac{5.5}{\sqrt{93}}}[/tex]
[tex]z = -1.75[/tex]
The test statistic is z = -1.75.
Do we reject the null hypothesis? Is there sufficient or insufficient evidence?
The pvalue of the test is the probability of finding a sample mean below 23, which is the pvalue of z = -1.75.
Looking at the z table, z = -1.75 has a pvalue of 0.0401
The pvalue of the test is 0.0401 > 0.02, which means that we do not reject the null hypothesis, as there is insufficient evidence.