Statistics and Advertising Week 5 Discussion

 Discussion Assignment Instructions

Statistics and Advertising

In Week 4, you explored t tests, which allowed you to compare a sample to a population or compare two groups to one another. You analyzed a study about how visualization techniques impact how long it takes people with insomnia to fall asleep. But what if you want to compare the effectiveness of more than two types of insomnia treatments? Analysis of variance, or ANOVA, allows you to do just that—compare multiple groups (called levels) based on an independent variable (called a factor). So in a study about insomnia treatments, you might compare a group that receives muscle relaxation training to a second group that receives visualization training and, finally, to a third group that receives deep breathing training. An ANOVA will allow you to compare all of the levels at once to see if, in general, the type of treatment influences how long it takes to fall sleep. Post hoc analyses can provide even more information by identifying which specific groups differ from one another, showing you which specific treatments are more effective than others.

In this Discussion you will use your knowledge of one-way ANOVAs to evaluate a research study scenario and make suggestions about what could be done to gain even better information.

Scenario:

The Alpha Shoe Company’s advertising department wants to publish an ad about a new basketball shoe it claims will enable athletes to jump higher. Alpha attributes this increase in lift to a new sole design, core, and tread.

An independent testing institute conducted a study on the shoe, called the “Pluto,” to determine if it really does result in higher jumping heights, in comparison to four other shoes. Five groups of four professional basketball players tested the shoes. The mean jumping height for each shoe was reported as follows:

1.     Pluto: 29.3 inches

2.     Omega II: 29.0 inches

3.     Beta Super: 28.7 inches

4.     Delta: 28.4 inches

5.     Gamma: 28.0 inches

Alpha did not report any inferential statistics in their ad, but it stated, “As you can clearly see, our Pluto shoes offer an obvious vertical lift advantage in comparison to other leading brands. Even a fraction of an inch can make all the difference in a big game!” Being the good consumer of research that you now are, what questions would you have after reading Alpha Shoe Company's ad?

Post  your explanation of

·         How the Alpha Shoe Company used the information they obtained from the testing institute.

·         What additional questions do you still have after reading the ad?

·          What did the researchers do correctly?

·          What criticisms do you have of the company’s approach?

·          Make a suggestion for a follow-up study that might be useful to the company and use ANOVA methodology as part of the approach.

·         Justify your post, using the Learning Resources.

It is very important to have the above questions answered and you can use any other reference in addition to the required reference.Thank you

Required reference

Welkowitz, J., Cohen, B. H., & Lea, R. B. (2012). Introductory statistics for the behavioral sciences (7th ed.). Hoboken, NJ: Wiley.

o    Chapter 12, “One-Way Analysis of Variance” (pp. 315–358)

This chapter goes into detail about ANOVA tests, testing for statistical significance among three or more means.

o    Chapter 13, “Multiple Comparisons” (pp. 349–371) 

This chapter explains how to make pairwise multiple comparisons of means and introduces Tukey’s HSD formula