Hi All,
I need help of calculating Sig T in Custom Tables.
I have a categorical variable with 10 categories and I want to calculate the Sig T of these categories with All Total of these. Is it possible to do so in SPSS CTABLES, if yes please suggest.
I have done the same in the below tables but it is not calculating problem. What algorithm SPSS use to calculate the Sig T.
I want to calculate the SiG T between Total Online and brand-1 to brand-4
|
Beauty |
|||||||||||
brand-1 |
brand-2 |
brand-3 |
brand-4 |
Total Online |
brand-5 |
brand-6 |
brand-7 |
Total Offline |
Total Category (Total Online + Total Offline) |
|||
Look and feel of the website/app : Q4X1_1: Q4 Again, thinking about when you shopped at < sGRIDYRET> for <sGRIDYCAT> , how satisfied
were you with the following attributes. Please use a scale from 0 to 10, where 0 is ‘Extremely dissatisfied’ an |
Answering Base |
Count |
147 |
128 |
113 |
117 |
505 |
0 |
0 |
0 |
0 |
505 |
Top 3 |
Count |
107 |
109 |
83 |
77 |
376 |
0 |
0 |
0 |
0 |
376 |
|
Column N % |
72.8% |
85.8% |
72.8% |
65.6% |
74.4% |
0.0% |
0.0% |
0.0% |
0.0% |
74.4% |
||
Rest |
Count |
40 |
18 |
31 |
40 |
129 |
0 |
0 |
0 |
0 |
129 |
|
Column N % |
27.2% |
14.2% |
27.2% |
34.4% |
25.6% |
0.0% |
0.0% |
0.0% |
0.0% |
25.6% |
||
Comparisons of Column Proportionsc,d,e |
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|
Beauty |
|||||||||||
brand-1 |
brand-2 |
brand-3 |
brand-4 |
Total Online |
brand-5 |
brand-6 |
brand-7 |
Total Offline |
Total Category (Total Online + Total Offline) |
|||
(A) |
(B) |
(C) |
(D) |
(E) |
(F) |
(G) |
(H) |
(I) |
(J) |
|||
Look and feel of the website/app : Q4X1_1: Q4 Again, thinking about when you shopped at < sGRIDYRET> for <sGRIDYCAT> , how satisfied
were you with the following attributes. Please use a scale from 0 to 10, where 0 is ‘Extremely dissatisfied’ an |
Top 3 |
|
D E J |
|
|
|
.a,b |
.a,b |
.a,b |
.a,b |
|
|
Rest |
|
|
|
B |
B |
.a,b |
.a,b |
.a,b |
.a,b |
B |
||
Results are based on two-sided tests with significance level .05. For each significant pair, the key of the category with the smaller column
proportion appears under the category with the larger column proportion. |
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a. This category is not used in comparisons because the sum of case weights is less than two. |
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b. This category is not used in comparisons because its column proportion is equal to zero or one. |
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c. Tests are adjusted for all pairwise comparisons within a row of each innermost subtable using the Bonferroni correction. |
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d. Cell counts of some categories are not integers. They were rounded to the nearest integers before performing column proportions tests. |
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e. Comparisons are not performed for some pairs where compared categories of a multiple response set contain identical sets of observations. |
Regards
Manoj
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