A.Courts Caribbean Limited is experiencing high level of delinquency among retail customers who buy on credit.As such, the company decided to pursue aggressive collection Programme through Reneto Adams Collection Agency. After3monthswithAdams,it wasobservedthatcollectionsdidnotimprove despite this aggression. The marketing manager then decided to use analytics to get a better understanding of these customers and argue that she will compare her delinquent customers with the non-delinquent to create profile of these customers. In assessing the point-of-sales and receivable systems, the following attributes were identified for comparison: income, installment amount, incidence of online payment, credit store and savings. The data was then analyzed using the independent sample t-test to determine the differences between delinquent and non-delinquent customers on each of the identified attributes. See Tables 2 and 3.

As, Data Scientist employed to Courts, prepare report for profiling delinquent vs. non-delinquent customers. In your report, you must attempt to explain these differences. [15 Marks]

Table 2. Group Statistics AR Status N Mean Std. Std. Error Deviation Mean Income non-delinquent 76 6.2632 1.38918 0. 15935 delinquent 28 12.8214 3.43245 0.64867 Installment non-delinquent 74 3.7568 1.03117 0. 11987 Amount delinquent 28 3.6071 1. 19689 0.22619 Incidence of non-delinquent 75 4.3467 0.74423 0.08594 Online Payments delinquent 28 4.0000 0.76980 0. 14548 Credit Score non-delinquent 74 3.6081 1.07037 0. 12443 delinquent 28 3.1786 0.77237 0. 1459 Savings non-delinquent 74 3.6081 1.07037 0. 12443 delinquent 28 3.1786 0.77237 0. 14596 Table 3. Independent Sample t-test Levene's Test for t-test for Equality of Means Equality of Variances F Sig. df Sig. (2-tailed) Income Equal variances assumed 25.983 0.000 -13.926 102 0.000 Equal variances not assumed 9.818 30.317 0.000 Installment Equal variances assumed 0.691 0.408 0.625 100 0.533 Amount Equal variances not assumed 0.584 43.040 0.562 Incidence of Equal variances assumed 1.123 0.292 2.084 101 0.040 Online Payments Equal variances not assumed 2.052 47.040 0.046 Credit Score Equal variances assumed 8.281 0.005 1.938 100 0.055 Equal variances not assumed 2.239 67.345 0.028 Savings Equal variances assumed 8.281 0.005 1.938 100 0.055 Equal variances not assumed 2.239 67.345 0.028