From time to time, unfortunately, Healthy Life employees have to deal with insurance fraud. Say,

some people claim medical services that have never been provided or money they never paid. To that

end, Healthy Life hired a number of investigators whose functions are not much different from those

of police detectives.

Doctor N.N. has been under suspicion for some time for deceiving both Healthy Life and his patients.

Healthy Life approached the provincial authorities and they agreed to launch a formal investigation

and open a case given a credible evidence of fraud is provided. The Healthy Life investigation

department found a number of offences.These included "up-coding" or "upgrading," which involved

billing for more expensive treatments than those actually provided; providing and subsequently

billing for treatments that were not medically necessary; scheduling extra visits for patients; referring

patients to another physician when no further treatment was actually necessary; "phantom billing," or

billing for services not rendered; and "ganging," or billing for services to family members or other

individuals who were accompanying the patient but who had not personally received any services.

Jennifer Nguyen took part in this investigation together with Dr. Steinberg and Ian McGillivray, a

former police detective and now a Healthy Life employee. At one point, Jennifer was asked to

compare the amount doctor N.N. charged for a certain medical procedure with the province average.

Jennifer randomly selected a sample of forty cases (see the Major Assignment Data file). Can we

support at 2% significance level the doctor's widely advertised claim that his average procedure fee

is way below the population average $520? Use Data Analysis t-Test: Two-Sample Assuming

Unequal Variances and "fool" Excel approach. Assume that the values are normally distributed.