Background:

An ANOVA can be used to see whether the mean reactions to different advertisements differ significantly (Green & Salkind 2016). For instance, if you are comparing three advertisements, you would want to determine if there is a substantial difference between their mean replies. Three advertisements will be evaluated in this scenario. The comparison groups will consist of the three advertisements.

The ANOVA will have a totally randomized design. Each advertisement will be viewed by the same amount of individuals, therefore a totally randomized design is suitable. The design of the ANOVA is crucial since it helps to compensate for intergroup variability. In this scenario, the three advertisements will be given at random to distinct groups of individuals. This will assist to control for any potentially confusing variables. Because we cannot anticipate which advertisement will have the highest response rate, the hypothesis is neutral.

We are only doing an experiment to determine whether there is a substantial variation in response rate between the three advertisements. Because we are testing for a difference in means across the three groups, the test would be two-tailed. This indicates that we are searching for a big disparity in either way. Similarly, one group may have a greater or lower mean response rate than the other two. The null hypothesis would be that there is no difference between the three commercials' response rates. The alternative hypothesis is that there is a substantial difference between the response rates of the three advertisements.

How will you measure the response rate?

References:

Green, S. B. & Salkind, N. J. (2016).Using SPSS for Windows and Macintosh(8^thed.). Pearson Education.