1. Were the groups in this study independent or dependent? Provide a rationale for your answer.
The groups in the research were dependent groups. This is because dependent groups are specific matching of subjects in one group to another. For the research, the information was comparing men verses women with the effects post MI, so specific members were chosen for both sample groups (men and women).
2. t = −3.15 describes the difference between women and men for what variable in this study? Is this value significant? Provide a rationale for your answer.
Mental health is the variable for the result of t= -3.15. This is significant because the larger the t score, the larger the difference in the groups. This score is the largest among all the other sections so it means mental health is the greatest amount of difference between men and women. That section also has the smallest p wave value, which also indicates significant findings because it shows a low chance of sample error.
3. Is t = −1.99 significant? Provide a rationale for your answer. Discuss the meaning of this result in this study.
Functioning health between men and women is measured in with the t score results of 1.99. This is significant statistically because it shows a difference between men and women and the p score is smaller than the alpha score witch was set at 0.05 for the study
4. Examine the t ratios in Table VI. Which t ratio indicates the largest difference between the males and females post MI in this study? Is this t ratio significant? Provide a rationale for your answer.
The mental health category had the largest difference between men and women, which was a t score of -3.15. The t ratio is significant because the largest the calculated t ratio is, the greatest the difference between the two groups.
5. Consider t = −2.50 and t = −2.54. Which t ratio has the smaller p value? Provide a rationale for your answer. What does this result mean?
-2.54 has a smaller p value, which was 0.007. The smaller the p value, the more significant the data
6. What is a Type I error? Is there a risk of a Type I error in this study? Provide a rationale for your answer.
A type 1 error occurs when the researcher rejects the null hypothesis when it is actually true. This can occur if the researcher runs multiple t tests to evaluate differences of various aspects of a study’s data. Yes there was a risk for a type 1 error because p value indicates 15 t tests were performed, but only 9 were