A mid‑size financial services firm has begun an AI‑driven wo…
A mid‑size financial services firm has begun an AI‑driven workforce transformation program. Leadership is worried about a growing skills gap: some employees are fluent with new AI tools (prompting, data analysis, workflow automation), while others still rely on traditional manual processes. To justify further investment in training, the company wants hard evidence that AI upskilling actually improves productivity. Employees were randomly divided into the two groups (training group and untrained group). Does completing the AI bootcamp significantly increase average productivity compared with employees who did not attend? Use the information below to complete a two-sample t CI. Make sure to define the parameter, state and check assumptions, state the interval and write an interpretation. > aggregate(AI_cases$`cases completed`, by = list(AI_cases$Group), FUN = sd) Group.1 x 1 trained 5.727347 2 untrained 5.884999 > t.test(AI_cases$`cases completed`~AI_cases$Group, var.equal = TRUE) Two Sample t-test data: AI_cases$`cases completed` by AI_cases$Group t = 3.8472, df = 76, p-value = 0.0002468 alternative hypothesis: true difference in means between group trained and group untrained is not equal to 0 95 percent confidence interval: 2.439920 7.677712 sample estimates: mean in group trained mean in group untrained 52.58250 47.52368