A sample of 26 offshore oil workers took part in a simulated escape exercise, and their escape time (unit: second) were observed. The sample mean and sample standard deviation are 370.69 and 24.36, respectively. Suppose the investigators had believed a priori that true average escape time would be at most 6 minutes. Does the data contradict this prior belief

Respuesta :

Answer:

[tex]t=\frac{370.69-360}{\frac{24.36}{\sqrt{26}}}=2.238[/tex]  

The degrees of freedom are given by:

[tex] df = n-1= 26-1=25[/tex]

And the p value would be:

[tex]p_v =P(t_{25}>2.238)=0.0172[/tex]  

If we use a 5% of significance level we have enough evidence to reject the null hypothesis and we can conclude that the true mean is significantly higher than 360 second or 6 minutes. We need to be careful since if we use a significance level of 1% the result change

Step-by-step explanation:

Information given

[tex]\bar X=370.69[/tex] represent the sample mean

[tex]s=24.36[/tex] represent the sample standard deviation

[tex]n=26[/tex] sample size  

[tex]\mu_o =6*60 =360 s[/tex] represent the value to verify

z would represent the statistic

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

Hypothesis to test

We want to check if the true mean is at most 360 seconds, the system of hypothesis would be:  

Null hypothesis:[tex]\mu \leq 360[/tex]  

Alternative hypothesis:[tex]\mu > 360[/tex]  

The statistic for this case would be given by:

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

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

[tex]t=\frac{370.69-360}{\frac{24.36}{\sqrt{26}}}=2.238[/tex]  

The degrees of freedom are given by:

[tex] df = n-1= 26-1=25[/tex]

And the p value would be:

[tex]p_v =P(t_{25}>2.238)=0.0172[/tex]  

If we use a 5% of significance level we have enough evidence to reject the null hypothesis and we can conclude that the true mean is significantly higher than 360 second or 6 minutes. We need to be careful since if we use a significance level of 1% the result change