In this example, a T-Test analysis of type T-Paired is performed on the fictitious banking data to analyze account usage.
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Parameterize a Parametric Test analysis as follows:
- Available Tables — twm_customer_analysis
- Statistical Test Style — T Paired
- First Column — avg_cc_bal
- Second Column — avg_sv_bal
- Group By Columns — age, gender
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Analysis Parameters
- Threshold Probability — 0.05
- Equal Variance — true (checked)
- Run the analysis.
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Click Results when it completes.
For this example, the Parametric Test analysis generated the following page. The paired t-test was computed on average credit card balance versus average savings balance, by gender and age. Ages over 33 were excluded for brevity. Results were sorted by age and gender in the listing below. The tests shows whether the paired values have mean differences which are not significantly different from zero for each gender-age combination. A ‘p’ means the difference was significantly different from zero. An ‘a’ means the difference was insignificant. The SQL is available for viewing but not listed below.
T-Test gender age D_F TTestPValue T TTestCallP_0.05 F 13 7 0.01 3.99 p M 13 6 0.13 1.74 a F 14 5 0.10 2.04 a M 14 8 0.04 2.38 p F 15 18 0.01 3.17 p M 15 12 0.04 2.29 p F 16 9 0.00 4.47 p M 16 8 0.04 2.52 p F 17 13 0.00 4.68 p M 17 6 0.01 3.69 p F 18 9 0.00 6.23 p M 18 9 0.02 2.94 p F 19 9 0.01 3.36 p M 19 6 0.03 2.92 p F 22 3 0.21 1.57 a M 22 3 0.11 2.25 a F 23 3 0.34 1.13 a M 23 3 0.06 2.88 a F 25 4 0.06 2.59 a F 26 5 0.08 2.22 a F 27 5 0.09 2.12 a F 28 4 0.06 2.68 a M 28 4 0.03 3.35 p F 29 4 0.06 2.54 a M 29 5 0.16 1.65 a F 30 8 0.00 4.49 p M 30 5 0.01 4.25 p F 31 5 0.04 2.69 p M 31 6 0.05 2.52 p F 32 5 0.05 2.50 a M 32 6 0.10 1.98 a F 33 9 0.01 3.05 p M 33 4 0.09 2.27 a