• Apply statistics to real world situations • Consider the ethical implications

Question

• Apply statistics to real world situations
   • Consider the ethical implications of statistics

Binomial probability distributions are used in business, science, engineering, and other fields. Suppose you work for a marketing agency and have to create a television ad for Brand A toothpaste. The toothpaste manufacturer claims that 40% of the toothpaste buyers prefer Brand A to Brand B. Your agency conducts a survey to check whether this claim is reasonable.

Respond to the following:

How would you do the sample survey?

Explain how you would conduct the survey.

What are the ethical implications if the manufacturer of Brand A toothpaste asked you to survey only its employees?

Considering this as a binomial distribution problem, how would you interpret the outcomes?

After conducting a random sample of people who do not work for the manufacturer, you found that 35/100 prefer Brand A. Could the manufacturer’s claim still be true?

Your random sample of 100 found only 25 people who preferred Brand A. If it is too unusual, would you still be justified in running the ad?

Explanation / Answer

There are many ways of sampling. One can go for simple random sampling, stratified sampling, systematic sampling.

Here systematic sampling can be used. Insead of asking buyers, you can choose retail stores which are in direct touch with the buyers.

A team is to be prepared. Divide the team into parts and collect information of the buying behaviour of customers. Questionnaire can be prepared.

Ethical considerations in research are critical. Ethics are the norms or standards for conduct that distinguish between right and wrong. They help to determine the difference between acceptable and unacceptable behaviors on the part of the researcher. Brand B toothpaste should not be degraded while conducting survey. Also it should be taken care that survey should be unbiased.

binomial distribution states that buyers might prefer Brand A over B or they might not. It might be a success or a failure.

Manufacturer claimed that 40% buyers prefer B over A.

35/100 indicates 35%. Hence manufacturer's claim does not hold true in this case. But, as it is a sample, the actual result might vary.

Running ad might increase the buyers. It might be a risk, but higher the risk, higher the returns,

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