Hypothesis Testing

Hypothesis testing typically begins with a theory, a claim, or an assertion about a particular parameter (mean or proportion) of a population.

The Federal Trade Commission (FTC) is an independent agency of the U.S. federal government charged with preventing unfair or deceptive trade practices. It regulates advertising, marketing, and consumer credit practices, and also prevents antitrust agreements and other unfair practices.

The FTC publishes press releases regularly about health and fitness claims athttps://www.ftc.gov/news-events/media-resources/truth-advertising/health-claims

Health and Fitness Claims. Retrieved from https://www.ftc.gov/news-events/media-resources/truth-advertising/health-claims

Find a claim about a product or service from one of the press releases listed in the FTC website.

Read through these and select one of interest to you that has not been picked by anyone else yet in class.

Initial Response: Formulating the Hypothesis

1. Summarize the advertising claim as shared in the media. What population parameter is the claim about? (Hint: Focus on a population mean or proportion, such as the mean weight of a cereal box, or the proportion of fast-food orders filled correctly.)
2. If you were to formulate a hypothesis test about this product/service, what would your null and alternative hypothesis be? (Be sure to use all the correct notations for Ho and Ha.)
3. State whether you have a one-tailed or two-tailed test (Be sure you use the correct inequality signs).

See Example post.

First response: Review one of your classmates’ post. In the context of their hypothesis test, discuss what the Type I Error and Type II Error would mean using a Decision Table as your guide. What level of significance would you suggest based on what a Type I Error or Type II Error would mean?

Recall that:

Type I Error is defined as rejecting the null hypothesis when in fact it should be accepted. (i.e. “False Positive,” “False Alarm,” defendant found guilty when in fact innocent)

Type II Error is defined as accepting the null hypothesis when in fact it should be rejected. (i.e. “False Negative,” defendant found not guilty when in fact guilty)

See Example post.

Second response: Review another classmate’s post. Suppose you are the researcher of the hypothesis test and you conclude to either “reject the null hypothesis” or “not to reject the null hypothesis.” Write a statement on your conclusion to the public about this service/product.

See Example post.

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