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CAISA Forum Question 878 A telecom company uses AI to improve its customer support operations. The AI analyzes customer complaints, service usage, escalation patterns, retention data, and support costs. It discovers that: 90% of customers receive satisfactory service and rarely complain. The remaining 10% of customers generate nearly 65% of complaints, escalations, and support costs. To address this, the AI proposes a major change: Allocate more support resources to the dissatisfied 10%. Prov
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CAISA Forum Question 877 If AI identifies spare capacity as waste, should it eliminate it? A large logistics company uses AI to optimize its delivery operations. The AI analyzes vehicle utilization, staffing levels, warehouse capacity, and route efficiency. It discovers that: Delivery vehicles are only utilized at 82% capacity on average. Certain warehouses appear underutilized. Extra staffing is maintained for demand spikes that occur only a few times each year. The AI recommends removing t
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Pradeep Shukla
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Showing content with the highest reputation on 08/11/2023 in Posts
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1 pointMann Whitney test This test is known as Wilcoxon rank-sum test. It is a non-parametric statistical test which is generally used to review the distributions between two independent groups. This is also an alternative to T-test, but we should use this test when our assumptions of normality and equal variances generally not met. This test is also applied to check that medians of two groups are statistically different from each other or not? This test works on below parameters: · Ranking · Calculating U · Comparison · Hypothesis testing · Interpretations Mann Whitney T test Assumptions No specific distribution assumptions Applied when data is non-normal and skewed. Comparing Rank between 2 groups Assumes data follows a normal distribution. Comparing with 2 groups with equal variances Real scenario where Mann-Whitney U test accepts more than T-test. ü When data is ordinal ü When we have small samples ü When we have outliers ü When our data is skewed ü When variances are not equal ü When we have categorical data to compare1 point
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