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A study was performed looking at the effect of mean ozone exposure on change in

ID: 3155250 • Letter: A

Question

A study was performed looking at the effect of mean ozone exposure on change in pulmonary function. Fifty hikers were recruited into the study; 25 study participants hiked on days with low-ozone exposure and 25 hiked on days with high-ozone exposure. The change in pulmonary function after a 4-hour hike was recorded for each participant. The results are given in the following table:

Comparison of change in FEV on high ozone vs. low ozone days

Ozone level

Mean change in FEV

sd

n

High

0.101

0.253

25

Low

0.042

0.106

25

What test can be used to determine whether the mean change in FEV differs between the high ozone and low ozone days?

Implement the test in the problem above and report a p-value (two-tailed).

Determine a 95% CI for: - true mean change in FEV on high ozone days - true mean change in FEV on low ozone days - true mean difference in change in FEV on high ozone days vs. low ozone days

PLEASE SHOW WORK - NO MINITAB! Thank you!

Comparison of change in FEV on high ozone vs. low ozone days

Ozone level

Mean change in FEV

sd

n

High

0.101

0.253

25

Low

0.042

0.106

25

Explanation / Answer

What test can be used to determine whether the mean change in FEV differs between the high ozone and low ozone days?

It is an independent two sample t test.

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Implement the test in the problem above and report a p-value (two-tailed).

Formulating the null and alternative hypotheses,              
              
Ho:   u1 - u2   =   0  
Ha:   u1 - u2   =/   0  
At level of significance =    0.05          
As we can see, this is a    two   tailed test.      
Calculating the means of each group,              
              
X1 =    0.101          
X2 =    0.042          
              
Calculating the standard deviations of each group,              
              
s1 =    0.253          
s2 =    0.106          
              
Thus, the standard error of their difference is, by using sD = sqrt(s1^2/n1 + s2^2/n2):              
              
n1 = sample size of group 1 =    25          
n2 = sample size of group 2 =    25          
Thus, df = n1 + n2 - 2 =    48          
Also, sD =    0.054861644          
              
Thus, the t statistic will be              
              
t = [X1 - X2 - uD]/sD =    1.075432589          
              
Also, using p values, as this is two tailed,              
              
p =    0.28755719   [ANSWER, P VALUE]      
              
As P > 0.05, WE FAIL TO REJECT THE NULL HYPOTHESIS.  

Hence, there is no significant difference between the mean change in FEV for high and low ozone levels. [CONCLUSION]

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Determine a 95% CI for: - true mean change in FEV on high ozone days - true mean change in FEV on low ozone days - true mean difference in change in FEV on high ozone days vs. low ozone days


For the   0.95   confidence level, then      
              
alpha/2 = (1 - confidence level)/2 =    0.025      
By table/technology,
  
t(alpha/2) =    2.010634758          
  
Thus,
          
lower bound = [X1 - X2] - t(alpha/2) * sD =    -0.051306729          
upper bound = [X1 - X2] + t(alpha/2) * sD =    0.169306729          
              
Thus, the confidence interval is              
              
(   -0.051306729   ,   0.169306729   ) [ANSWER]

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Hi! If you use another method/formula in calculating the degrees of freedom in this t-test, please resubmit this question together with the formula/method you use in determining the degrees of freedom. That way we can continue helping you! Thanks!

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