Write your research (alternative) hypothesis here Ha: Men MICA score Women MICA score What two means are you comparing? The two means I would be comparing are the mean MICA score for men vs.. The mean MICA score for women. Is your test one-tailed or two-tailed? My test is a two-tailed test because the alternative hypothesis is looking at where the MICA score for men and women are not equal. B. Samples and Populations: Given your research question and hypothesis above, what would your population of interest be? Describe your population.
My population of interest is: men and women between the ages of 22 and 30 that have taken the MICA one time. Describe the population – what does it contain? The population contains men and women ages 22 to 30. To test your research hypothesis, describe the sample you might collect, including sampling method and size. How big is the sample? The sample size is 30 people, 15 women and 15 men. How might you collect this sample (using what method)? The method could to collect this data would be to do a survey of medical students who have already taken the MICA.
Using your hypothesis test, sample size, and alpha as . 05, use the appropriate table in the Appendix of the textbook to determine the cut-off critical value(s) for your rejection region. Since our degrees of freedom is n-l, we use 29, instead of 30 on our t-distribution table. Using degrees of freedom and our alpha as . 05, we can find that the cut-off critical value is 2. 045 for the rejection Oregon. C. Considering Errors: Assume that you reject your null hypothesis. Describe the error that you would make in terms of your research question and conclusion, if oh made a Type I error.
What is a Type I error? A Type I error is when the null hypothesis is rejected, even though it is in fact true. In terms of your research question, what would it mean to make a Type 1 error? For this particular research question, a Type I error would mean that my sample was incorrect in stating that men and women have equal MICA scores, but in actuality, they do have the same scores. This error can happen for various reasons, including but not limited to, small sample size and improper data collection.
Describe the error that you would make in terms of our research question and conclusion, if you made a Type II error. Which type of error is worse, and why? What is a Type II error? A Type II error is when the null hypothesis is not rejected, when in fact the alternative hypothesis is true. In terms of your research question, what would it mean to make a Type II error? In terms of my research, with a Type II error, I conclude that the mean MICA score for men is the same as the mean MICA score for women. However, this is not actually the case.
The mean MICA score for men and women are not equal. Which error type is worse in your case and why? A Type I error would be worse for my research because if we start with the assumption that most people believe men do better on the MICA (and are better at science) overall than women do, a Type I error would prove them right, thus continuing to perpetuate that idea. A Type I error would give that false hope that men and women do not perform equally on the MICA. D. Power and Effect Size: Suppose the effect size of your research study is very large. What does this tell you in your case?
What can you say about your sample mean versus the population mean? How does the sample size and effect size alter the Power of a study? If the effect size of my research study is large, then know that my data is significant. Having a large sample size of 30 and a large effect will allow the power of my study to be large and statistically significant. E Submit: Paste your completed Word Document to this area. If your SPAS item(s) do not paste properly, also attach your full Word document to your post, and note in your post that the SPAS items are attached.
