Question

In: Statistics and Probability

A large national survey of American dietary habits showed a mean calorie consumption of 2700 kcal...

A large national survey of American dietary habits showed a mean calorie consumption of 2700 kcal and a standard deviation of 450 kcal among teenage boys. You are studying dietary habits of children in your county to see if they differ from the national norm.
(a) In a sample of 36 teenage boys, you find a mean consumption of 2620 kcal. At  = 0.05, is this significant evidence that the mean in your county differs from the national mean? Assume that the standard deviation observed nationally can be used for  .
(b) Using =0.05 and sample of size 36, what is the probability that you will actually be able to detect a situation where your county has a mean of only 2600 kcal? (That is, what is the power if =2600?)

Solutions

Expert Solution

a)

Ho :   µ =   2700                  
Ha :   µ ╪   2700       (Two tail test)          
                          
Level of Significance ,    α =    0.050                  
population std dev ,    σ =    450.0000                  
Sample Size ,   n =    36                  
Sample Mean,    x̅ =   2620.0000                  
                          
'   '   '                  
                          
Standard Error , SE = σ/√n =   450.0000   / √    36   =   75.0000      
Z-test statistic= (x̅ - µ )/SE = (   2620.000   -   2700   ) /    75.0000   =   -1.067
                          
  
p-Value   =   0.2861   [ Excel formula =NORMSDIST(z) ]              
Decision:   p-value>α, Do not reject null hypothesis                       
Conclusion: There is not enough evidence that the mean in your county differs from the national mean

b)

true mean ,    µ =    2600                          
                                  
hypothesis mean,   µo =    2700                          
significance level,   α =    0.05                          
sample size,   n =   36                          
std dev,   σ =    450.0000                          
                                  
δ=   µ - µo =    -100                          
                                  
std error of mean,   σx = σ/√n =    450.0000   / √    36   =   75.00000          
                                  
Zα/2   = ±   1.960   (two tailed test)                      
We will fail to reject the null (commit a Type II error) if we get a Z statistic between                           -1.960   and   1.960
these Z-critical value corresponds to some X critical values ( X critical), such that                                  
                                  
-1.960   ≤(x̄ - µo)/σx≤   1.960                          
2553.003   ≤ x̄ ≤   2846.997                          
                                  
now, type II error is ,ß =        P (   2553.003   ≤ x̄ ≤   2846.997   )          
       Z =    (x̄-true mean)/σx                      
       Z1 = (   2553.003   -   2600   ) /   75.00000   =   -0.627
       Z2 = (   2846.997   -   2600   ) /   75.00000   =   3.293
                                  
   so, P(   -0.627   ≤ Z ≤   3.293   ) = P ( Z ≤   3.293   ) - P ( Z ≤   -0.627   )
                                  
       =   1.000   -   0.265   =   0.7341   [ Excel function: =NORMSDIST(z) ]  
                                  
power =    1 - ß =   0.2659                          


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