Dennis Barry, a hospital administrator, has examined past records from 210 randomly selected 8-hour shifts to determine the frequency with which the hospital treats fractures. The numbers of days in which zero, one, two, three, four, or fi ve or more patients with broken bones were treated were 25, 55, 65, 35, 20, and 10, respectively. At the 0.05 level of signifi cance, can we reasonably believe that the incidence of broken-bone cases follows a Poisson distribution with λ = 2?
A large city fire department calculates that for any given precinct, during any given 8-hour shift, there is a 30 percent chance of receiving at least one fi re alarm. Here is a random sampling of 60 days:
A diligent statistics student wants to see whether it is reasonable to assume that some sales data have been sampled from a normal population before performing a hypothesis test on the mean sales. She collected some sales data, computed x = 78 and s = 9, and tabulated the data as follows: