In: Statistics and Probability
Q 6       A STUDY WAS CONDUCTED TO
DETERMINE IF THERE IS A SIGNIFICANT RELATIONSHIP BETWEEN THE
FREQUENCY OF MEAT SERVED AS A MAIN MEAL PER MONTH FOR INDIVIDUALS
LIVING IN THE FOUR SECTIONS OF THE UNITED STATES. A QUESTIONAIRE
WAS ADMINISTERED TO A RANDOM SAMPLE OF 400 FAMILIES AND THE RESULTS
ARE SUMMARIZED BELOW      
           
           
          
           
           
   
          
           
           
   
          
           
           
   
          
           
           
   
           FREQUENCY OF
MEAT AS A MAIN MEAL PER MONTH      
           
       
       LIVING AREA   LESS THAN
11   11 TO 20   MORE THAN 20   ROW
TOTALS          
   
       EASTERN   46  
36   20   102      
       
       SOUTH    40  
40   26   106      
       
       WESTERN    16  
38   38   92      
       
       NORTH   25  
36   39   100      
       
       COLUMN TOTALS  
127   150   123   400  
           
          
           
           
   
       DO THESE SAMPLE RESULTS INDICATE
THAT THERE IS A SIFNIFICANT RELATIONSHIP BETWEEN THE FREQUENCY OF
MEAT SERVED AS A MAIN MEAL PER MONTH AND GEOGRAPHIC LIVING AT ALPHA
= 0.01          
           
       
          
           
           
   
          
           
           
   
First we compute the expected frequency for each of the 12 cells
here as:
Ei = (Sum of column i)*(Sum of row i) / Grand Total
These are computed in the circular brackets below as:
The chi square test statistic
contribution here is computed as:

These are given in the square bracket in the given table.
These are summed to obtain the chi square test statistic here as:

Degrees of freedom here is computed as:
Df = (num of rows - 1)*(Num of columns - 1) = (4 - 1)*(3 - 1) =
6
Therefore the p-value is now obtained from the chi square distribution tables here as:

As the p-value here is 0.000235 < 0.01 which is the level of significance, therefore the test is significant here and we can reject the null hypothesis here. Therefore we have sufficient evidence here that the two variables are associated here that is not independent.