Research Methods

Provide examples of how the t test and ANOVA could be used to compare means within your work environment or domain of interest. Discuss the appropriateness of using the t test versus ANOVA.

Please include the name of the person or question to which you are replying in the subject line. For example, “Tom’s response to Susan’s comment.”

Friendly reminder to begin your Discussion Initial Post as early in the week as possible. Waiting till the end of the Unit sacrifices your learning, sharing and communication with one another.

Kindly address the discussion question(s) submitting a reflective response. Reflective defined is characterized by or manifesting careful thought : a thoughtful essay. occupied with or given to thought ; contemplative; meditative; reflective: in a thoughtful mood, careful, heedful, or mindful.

Looking forward to reading each of your posts and comments.


An example of using the ANOVA can be around 3 regions or counties and which one drinks the most alcohol (as part of the example, it’d be interesting if at least 1 county was a dry-county). The hypothesis can be that all the counties drink the same amount of alcohol, and the alternative can be that not all the counties would drink the same amount of alcohol (which is why it would be interesting to have at least 1 county by “dry”). The ANOVA can then be tested on and it can be determined if there is a larger and smaller consumer of alcohol among the 3 counties. This testing would be more appropriate for ANOVA since ANOVA will determine whether >= 3 populations are statistically different from each other.

An example of t-test can be used to compare the grades of 2 groups of students for this research methods class; the first population can be this class that we’re all in, and the other population can be a group of students from a past class earlier in the year. The test can be whether there is a statistically significant difference between the scores of the 2 groups. Because there are only 2 populations, the t-test would be more appropriate than ANOVA.

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