Pharmaceutical companies are continually searching for new drugs. Testing the thousands of compounds for the few that might be effective is known in the pharmaceutical industry as drug screening. Dunnett (1978) views the drug-screening procedure in its preliminary stage in terms of a statistical decision problem: “In drug screening, two actions are possible: (1) to ‘reject’ the drug, meaning to conclude that the tested drug has little or no effect, in which case it will be set aside and a new drug selected for screening; and (2) to ‘accept’ the drug provisionally, in which case it will be subjected to further, more refined experimentation.”* Since it is the goal of the researcher to find a drug that affects a cure, the null and alternative hypotheses in a statistical test would take the following form: 

H_o: Drug is ineffective in treating a particular disease 

H_a: Drug is effective in treating a particular disease 

Dunnett comments on the possible errors associated with the drug-screening procedure: “To abandon a drug when in fact it is a useful one (a false negative) is clearly undesirable, yet there is always some risk in that. On the other hand, to go ahead with further, more expensive testing of a drug that is in fact useless (a false positive) wastes time and money that could have been spent on testing other compounds.”

a. A false negative corresponds to which type of error, Type I or Type II?

b. A false positive corresponds to which type of error, Type I or Type II?

c. Which of the two errors is more serious? Explain.