The following prices, in dollars, of 7.5-cubic-foot refrigerators were recorded from a random sample. 314 305 344 283 285 310​ 383​ 285​ 300​ 300 A consumer organization reports that the mean price of 7.5-cubic-foot refrigerators is greater than $300. Do the data provide convincing evidence of this claim? Use the α = 0.05 level of significance and assume the population is normally distributed.

Answer :

Answer:

[tex]t=\frac{310.9-300}{\frac{31.09}{\sqrt{10}}}=1.109[/tex]      

The degrees of freedom are given by:

[tex]df=n-1=10-1=9[/tex]  

And the p value would be given by:

[tex]p_v =P(t_{9}>1.109)=0.148[/tex]  

Since the p value is higher than the significance level of 0.05 we don't have enough evidence to conclude that the true mean is significantly higher than $300 because we FAIL to reject the null hypothesis.

Step-by-step explanation:

Information given

314 305 344 283 285 310​ 383​ 285​ 300​ 300

We can calculate the sample mean and deviation with the following formula:

[tex]\bar X =\frac{\sum_{i=1}^n X_i}{n}[/tex]

[tex]s =\sqrt{\frac{\sum_{i=1}^n (x_i -\bar X)^2}{n-1}}[/tex]

[tex]\bar X=310.9[/tex] represent the sample mean      

[tex]s=31.09[/tex] represent the standard deviation for the sample      

[tex]n=10[/tex] sample size      

[tex]\mu_o =300[/tex] represent the value to test

[tex]\alpha=0.05[/tex] represent the significance level

t would represent the statistic

[tex]p_v[/tex] represent the p value

Hypothesis to test

We want to verify if the true mean is greater than 300, the system of hypothesis would be:      

Null hypothesis:[tex]\mu \leq 300[/tex]      

Alternative hypothesis:[tex]\mu > 300[/tex]      

The statistic is given by:

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

Replacing the info given we got:

[tex]t=\frac{310.9-300}{\frac{31.09}{\sqrt{10}}}=1.109[/tex]      

The degrees of freedom are given by:

[tex]df=n-1=10-1=9[/tex]  

And the p value would be given by:

[tex]p_v =P(t_{9}>1.109)=0.148[/tex]  

Since the p value is higher than the significance level of 0.05 we don't have enough evidence to conclude that the true mean is significantly higher than $300 because we FAIL to reject the null hypothesis.

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