EXERCISE 29 Questions to be Graded
1. Were the groups in this study independent or dependent? Provide a rationale for your answer.
The two groups were independent since they were formed based on gender with no intent to match subjects on any variable. The men and women selected didn’t share any relationship or live in the same location.
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.
In this study, t= -3.15 describes the mental health variable. It is significant because they are the variables being tested since the p value is 0.002 and the alpha is 0.05, the difference can cause the null hypothesis to be rejected.
3. Is
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There is a risk for a type 1 error in this study because of the multiple comparisons in this study.
7. Should a Bonferroni procedure be conducted in this study? Provide a rationale for your answer.
There are multiple values being considered in this study. This has the potential to cause a type 1 error and Bonferroni procedures should be used to reduce the risk of a type 1 error from happening.
8. If researchers conducted 9 t-tests on their study data. What alpha level should be used to determine significant differences between the two groups in the study? Provide your calculations.
If 9 t tests were conducted and the set alpha for this study is 0.05, then the alpha level that should be used to determine the differences between the two groups is 0.05/9=0.0056 and the resulting alpha will be used to determine significant differences.
9. The authors reported multiple df values in Table VI. Why were different df values reported for this study?
Different df values were reported due to some study participants not participating in all areas of the study. This can cause a difference in the overall scores of the study.
10. What does the t value for the Physical Component Score tell you about men and women post MI? If this result was consistent with previous research, how might you use this knowledge in your practice?
The t value for the physical component score implies that men and women post MI had different
So, we should reject the null hypothesis H0. At a 0.05 level of significance level, we conclude that there is a significant difference between the average height for females and the average height for the males.
· What conclusions did the study reach? Are the conclusions appropriate? Why or why not?
7. If a study had a result of F(2, 147) = 4.56, p = 0.003, how many groups were in the study, and what was the sample size?
Reporting t values- when you have already reported p values- is not necessary and can cause confusion.
An alpha level of 0.05 is arbitrary and was set as a standard by scientists. One of the key concepts in hypothesis testing is that of significance level or, the alpha level, which specifies the probability level for the evidence to be an unreasonable estimate. Unreasonable means that the estimate should not have taken its particular value unless some non-chance factor(s) had operated to alter the nature of the sample such that it was no longer representative of the population of interest. (Price, 2000)
Gender – whether there was a difference in performance between genders; used for comparison between male and female participants
It tells that the t-statistic with 97 degrees of freedom was 2.14, and the corresponding p-value was less than .05, specifically around 0.035. Therefore, it is appropriate to conclude the research study was statistically significant.
However, treatment four, 0.1296 (±0.608), represents that the mean was extraneous from what it should be (Table 1). The t-tests show how different the mean is in each treatment.
9. If there were 32 subjects in the experimental group and 36 subjects in the control group, why is the income data only reported for 30 subjects in the experimental group and 34 subjects in the control group? Based on the “Note” at the bottom of Table 1, Numbers do not always total 32 for the experimental group or 36 for control group because of missing data.
| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are
With a P-value of 0.00, we have a strong level of significance. No additional information is needed to ensure that the data given is accurate.
The t value tells us about the differences between men and women post MI physical component score. In my practice using this t value, I would be able to work differently between men and women after post MI. Teaching might provide to women more about physical functioning, role physical, bodily pain and general health since these are all included in physical component score. The physical component score for women is 48.5 compared to men 51.1 (standard deviation). Therefore, women might need to educate more about the
For this independent t test, the mean GPAs of 64 females and 41 males were compared. The variables used are (1) gender, and (2) GPA. The predictor, or independent, variable is gender. And the outcome variable is GPA. Gender can only have two values, male or female; this
In this case, level of significance, α was not provided. Therefore, the analysis will be evaluated based on two α values which are:
There were also issues with the groups of participants that took part in the study because there were three groups, T1, T2, and T3, that were involved in the study, but not all of the groups were tested for all conditions of the study and there were different numbers of participants in each group as well. Though T2 and T3 stemmed from T1, the groups still had different number of participants because of the lower response rates (Iyengar, Wells, & Schwartz, 2006). Lastly, a