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mart [117]
3 years ago
8

The number of "destination weddings" has skyrocketed in recent years. For example, many couples are opting to have their wedding

s in the Caribbean. A Caribbean vacation resort recently advertised in Bride Magazine that the cost of a Caribbean wedding was less than $30,000. Listed below is a total cost in $000 for a sample of 8 Caribbean weddings. At the 0.10 significance level, is it reasonable to conclude the mean wedding cost is less than $30,000 as advertised?
29.1 28.5 28.8 29.4 29.8 29.8 30.1 30.6

Required:
a. State the null hypothesis and the alternate hypothesis. Use a 0.10 level of significance.
b. State the decision rule for 0.10 significance level.
c. Compute the value of the test statistic.
d. What is the conclusion regarding the null hypothesis?
Mathematics
1 answer:
vladimir2022 [97]3 years ago
8 0

Answer:

a) Null hypothesis:\mu \geq 30  

Alternative hypothesis:\mu < 30  

b) Since we are conducting a left tailed test we need to find a quantile in the normal distribution who accumulates 0.1 of the area in the left and we got:

z_{cric}= -1.28

If the calculated value is lower than -1.28 we have enough evidence to reject the null hypothesis.

c) t=\frac{29.51-30}{\frac{0.698}{\sqrt{8}}}=-1.986    

d) Since the calculated value is lower than the critical value we have enough evidence to reject the null hypothesis at the significance level of 10%. So then the true mean is significantly lower than 30000 for this case.

Step-by-step explanation:

Data given and notation  

For this case we have the following data:

29.1 28.5 28.8 29.4 29.8 29.8 30.1 30.6

We can calculate the mean and deviation with these formulas:

\bar X = \frac{\sum_{i=1}^n X_i}{n}

s = \sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}

\bar X=29.51 represent the sample mean

s=0.698 represent the sample standard deviation

n=8 sample size  

\mu_o =30 represent the value that we want to test

\alpha=0.1 represent the significance level for the hypothesis test.  

t would represent the statistic (variable of interest)  

p_v represent the p value for the test (variable of interest)  

Part a: State the null and alternative hypotheses.  

We need to conduct a hypothesis in order to check if the true mean is less than 30000, the system of hypothesis would be:  

Null hypothesis:\mu \geq 30  

Alternative hypothesis:\mu < 30  

Part b

Since we are conducting a left tailed test we need to find a quantile in the normal distribution who accumulates 0.1 of the area in the left and we got:

z_{cric}= -1.28

If the calculated value is lower than -1.28 we have enough evidence to reject the null hypothesis.

Part c

The statistic is given by:

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}  (1)  

We can replace in formula (1) the info given like this:  

t=\frac{29.51-30}{\frac{0.698}{\sqrt{8}}}=-1.986    

Part d

Since the calculated value is lower than the critical value we have enough evidence to reject the null hypothesis at the significance level of 10%. So then the true mean is significantly lower than 30000 for this case.

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