A researcher compares men's and women's attitudes toward "road rage." Specifically, college students are asked to read a brief scenario describing a road rage incident in which a driver of a car attempts to scare a bicycle rider who accidentally cut across his path. The driver aims his car at the bicyclist and the bicycle rider, in an attempt to get out of the way, falls and gets hurt. Men and women rate how much they are disturbed by the driver's reaction using a 10-point scale (1 = not disturbed at all, 10 = very disturbed). The mean for men was 7.4 and the mean rating for women was 8.6. A t-test for independent groups indicated the following result: t(28) = 2.76, p = .01. Answer the following questions about the results of this hypothetical experiment.
1. Were the results statistically significant?
2. How many men and women were there in this study (assuming equal numbers in each condition)?
3. What does the p value tell you in addition to the fact that the results may be considered statistically significant?
4. Is a Type II error possible in this study?
5. What should the researcher report along with the results of the t-test?© BrainMass Inc. brainmass.com September 20, 2018, 6:49 pm ad1c9bdddf - https://brainmass.com/statistics/hypothesis-testing/interpreting-the-null-hypothesis-significance-test-nhst-351256
1. Were the results statistically significant? Yes (p < .05)
2. How many men and women were there in this study (assuming equal numbers in each condition)? df (28)= N - 2 so N= 30 total (15 men and 15 woman)
3. What does the p value tell you in addition to the fact that the results may be considered statistically significant? What the level of confidence is (99%)
4. Is a Type II error possible in this study? No, we rejected the null so we can only make a Type I error.
5. What should the researcher report along with ...
Interpreting the Null hypothesis significance test, especially using everyday language can be hard. This answer guides you through how to read and interpret a finding (like from an article) and gives you an example of practical significance (versus statistical significance).