A pharmaceutical firm recently announced a new drug to treat people with debilitating diseases. None of the current drugs (drugs B, C, D, and E) on the market, along with this drug (drug A), can cure this disease. These drugs, along with drug A, are designed to subdue any pains derived from this disease and prolong that duration for patients free from pain. The primary metric is to establish efficacy of a drug is to measure how long patients can be pain free once taken. This pharmaceutical company that has developed this new drug, drug A, claims that it is a more effective drug than all the other drugs in the market. The company specifically claims that 68% of all patients tested with this drug, drug A, is effective in subduing pains for relatively long periods of time. A team of doctors at the University of X randomly tested 196 patients who suffer from this disease and use drug A to determine its efficacy rate. Of the 196 patients tested, 145 did find drug A to be effective. This same team of doctors at the University of X Medical School is now trying to establish if there is any difference in how effective drug A compared to other patients who also suffer from that same debilitating disease but are prescribed to take these other drugs. The data is shown below. A B C D E Effective 145 84 106 118 98 Non-effective 51 16 48 26 22 (a) At the 2% level of significance, is there a difference in the proportions of patients who are taking drugs (A - E) as far patients reporting how effective these drugs are? (b) Estimate the p value for this test and what can you infer from this? (c) Redo this test by adjusting the level of significance to 1%. What can you conclude from this? Is there any indication to show that drug A is more effective than any of the other drugs currently in the market?