Daniel Jean-Baptiste Is the Brand Manager for Healthy-Pick Cookies, Inc

Daniel Jean-Baptiste is the brand manager for Healthy-Pick Cookies, Inc. Daniel had been through the new product development process and has developed a new cookie that has very good taste and texture, yet has no calories, fat, sodium, or cholesterol. Concept tests on the product have been excellent and now Daniel is ready to test market the new cookie and has selected Vancouver, British Columbia, as his first test city. But before he starts the test market, Daniel wants to conduct a research project that will help him forecast sales, so that he can better prepare production to supply the test market. The project leads to a probability sample in which household members are randomly called and are given a thorough description of the new cookie, including the price and choices of flavours. The key question respondents are asked is how likely it is that they will actually buy the new cookie, and this is measured on a 7-point intensity continuum scale ranging from 1 being "Very Unlikely" to 7 being "Very Likely". Respondents were also asked how many boxes of cookies they would expect to buy in a month. At the end of the study, the researchers tell Daniel that 8 percent of the households contacted stated that they were "Very Likely" to buy the new cookie. In order to get an estimate of the sales potential in the test market Daniel could:

A) take 8 percent of all the households in Vancouver and multiply this times the population parameter.
B) use the 8 percent as the "best estimate" times the number of households in the market and multiply this number by the average number of boxes expected to be purchased.
C) use the 8 percent as the "best estimate" times the number of households in the market and divide this number by the average number of boxes expected to be purchased.
D) use the 8 percent as the "best estimate" times the number of households in the market and multiply this number by the average number of boxes expected to be purchased. In addition, use the upper and lower limits of a hypothesis test to calculate a pessimistic and optimistic estimate respectively.
E) use the 8 percent as the "best estimate" times the number of households in the market and multiply this number by the average number of boxes expected to be purchased. In addition, use the upper and lower limits of a confidence interval around the "best estimate" to calculate optimistic and pessimistic estimates respectively.