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Question 857:

1

Answer:

No answer provided yet.We will use a Chi-Square test of independence to determine if there is a relationship between packaging size and economic status. The Null Hypothesis for this test is that there is no relationship between the two variables (they are independent). We will reject the Null Hypothesis if we obtain a p-value of less than .05.

The test statistic, Chi-Square, is found by subtracting the expected value from the observed value, squaring this difference, then dividing by the expected value. You add this value up for all the cells in the table.

First we compute the column totals and row totals.
   Lower  Middle  Upper  Row Total
 Small  24  22  18  64
 Medium  23  28  19  70
 Large  18  27  29  74
 Jumbo  16  21  33  70
   81  98  99  278

Expected Values
Expected values are found by multiplying the row total by the column total and dividing by the total for the table.

   Lower  Middle  Upper
 Small 18.647
22.56
22.79
 Medium 20.39
24.67
24.93
 Large 21.56
26.08
26.35
 Jumbo 20.39
24.67
24.92

Now we subtract the expected counts from the actual counts from the first table, square it and divide by the expected.

   Lower  Middle  Upper
 Small 1.53
.013
1.007
 Medium .3325
.447
1.41
 Large .588
.032
.2659
 Jumbo .947
.547
2.61

Finally we add up all the values in the 3rd table to get the Chi-Square test statistic of 9.74. We evaluate its significance using the degrees of freedom found as the (# of rows-1)*(# of cols -1) = 2*3 = 6. Looking up the significance of the chi-square value using a table or the excel function = CHIDIST(9.74,6) we get the p-value of .1359.

Since the p-value is above the alpha cutoff of .05 we FAIL to reject the Null and conclude there is not enough evidence to conclude the variables are related. In other words, there is not a significant relationship between packaging preference and economic status.

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