Level of measurement sample essay
1. What demographic variables were measures at least at the interval level of measurement? a. The number of hours worked per week and the length of labor (hrs)
2. What statistics were used to describe the length of labor in this study? Were these appropriate? a. Length of labor for both the control and experimental groups were described with mean and standard deviations. Yes, these were appropriate measures of statistics.
3. What other statistics could have been used to describe the length of labor? Provide a rationale for your answer. a. In addition to mean and standard deviations, mode could have been used in this study to describe length of labor. It would have given an understanding as to how long the common length of labor was. Median could have also been used, but I don’t think it would be any more beneficial than knowing the average and most common length of labor.
4. Were the distributions of scores similar for the experimental and control groups for the length of labor? Provide a rationale for your answer. a. The standard deviation for the experimental and control groups were 7.78 and 7.2 hours, respectively. By looking at standard deviation, yes the distribution of scores appear similar. However, when looking at the average length of hours for these groups, the experimental group’s length of labor was almost 2 hours longer which I feel is quite a significant difference. Each group must have similar outliers to have affected the standard deviation in such a way to make them so similar.
5. Were the experimental and control groups similar in their type of feeding? Provide a rationale for your answer. a. Yes, bottle feeding was the most common type of feeding used in both the experimental and control group. The experimental group chose bottle 53.1%, breast feeding 40.6% and both 6.3%. The control group chose bottle 50.0%, breast feeding 41.7%, and both 5.6%. Each group had the highest use of bottle, second highest use of breast feeding, and lowest use for both manners of feeding.
6. What was the marital status mode for the subjects in the experimental and control groups? Provide both the frequency and percentage for the marital status mode for both groups. a. Married was the highest mode for both groups. The experimental group had a frequency of 25 married (78.1%), 1 separated/divorced (3.1%), and 6 single (18.8%). The control group had a frequency of 31 married (86.1%), 1 separated/divorced (2.8%), and 3 single (8.3%).
7. Could a median be determined for the education data? If so, what would the median be for education for the experimental and the control groups? Provide a rationale for your answer. a. Yes, a median can be determined for the education data. In the experimental group: 7 had high school education, 11 had some college, and 14 were a college graduate or higher. The median for the experimental group is 11 – some college. In the control group: 6 had high school education, 13 were a college graduate or higher, and 15 had some college. The median for the control group is 13 – college graduate or higher.
8. Can the findings from this study be generalized to Black women? Provide a rationale for your answer. a. Yes, in the experimental group there was only 1 Black woman accounted for and in the control group there were none. Since there are predominantly white women in this study (92% in the experimental and 96.55% in the control group), we are unable to rationalize findings from one black participant.
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? a. We are missing variables, as stated in the Relevant Study Results, “a total of 80 women were initially enrolled.. twelve of these women dropped out of the study resulting in the final sample of 68.” There is missing data for the control group.
10. Was the sample for this study adequately described? Provide a rationale for your answer. a. No, the sample for this study was inadequately described due to missing data. The experimental group numbers do not all add up to 32. The control group does not have 36 subjects. The percentages describing this sample do not add up to 100%. Therefore they are not accurately describing the data given because not all of the subject’s data was accounted for in all categories (race, marital status, education, etc.).
1. The researchers analyzed the data they collected as though it were at what level of measurement? a. Interval/ratio
2. What was the mean posttest empowerment score for the control group a. The average was 97.12, SD was 8.73
3. Compare the mean baseline and posttest depression scores of the experimental group. Was this an expected finding? Provide a rationale for your answer. a. Yes, this was an expected finding. The mean baseline (14.0) and the posttest depression (13.36) scores difference = 0.64. This value shows that the empowerment program decreases depression. 4. Compare the mean baseline and posttest depression scores of the control group. Do these scores strengthen or weaken the validity of the research results? Provide a rationale for your answer. a. The control groups mean baseline score and posttest depression scores were both 10.40. These unchanging scores of the control group indicate to me that the empowerment program does not decrease nor increase depression.
5. Which group’s test scores had the least amount of variability or dispersion? Provide a rationale for your answer. a. The control group’s test scores had the least amount of variability or dispersion. There weren’t any changes in depression scores as the baseline SD = 10.34, and the posttest SD = 10.34 as well. The experimental group SD changed from 11.31 to 10.55 with the empowerment techniques though.
6. Did the empowerment variable or self-care self-efficacy variable demonstrate the greatest amount of dispersion? Provide a rationale for your answer. a. The self-care self-efficacy variable demonstrated greater dispersion than the empowerment variable. b. Empowerment: SD 9.19 – 7.28 = 1.91 in the experimental group and SD 8.99 – 8.73 = 0.26 in the control group so.. i. 1.91 + 0.26 = 2.17
c. Self-care self-efficacy: SD 14.88 – 13.55 = 1.33 in the experimental group and SD 13.62 – 10.55 = 3.07 in the control group so.. i. 1.33 + 3.07 = 4.4 d. 4.4 > 2.17. Self-care self-efficacy’s higher score of 4.4 shows the greatest amount of dispersion.
7. The mean is a measure of an average value of a distribution while the SD is a measure of dispersion (how much the scores are spread) of its scores. Both X and SD are descriptive statistics.
8. What was the mean severity for renal disease for the research subjects? What was the dispersion or variability of the renal disease severity scores? Did the severity scores vary significantly between the control and the experimental groups? Is this important? Provide a rationale for your answer. a. Mean severity = 6.74
b. Severity variability = 2.97
c. Yes, the severity scores vary significantly between the control and the experimental group. d. Yes, this is important because for one, the study focuses on the severity differences between these two groups. This study showed that there were significant differences in the improvement of each variable (empowerment, self-care self-efficacy, and depression) in the experimental group.
9. Which variable was least affected by the empowerment program? Provide a rationale for your answer. a. The depression variable for the empowerment program was least affected. In the experimental group the baseline depression (14.00) hardly changed from the posttest depression (13.36). In the control group, the depression variable did not change at all, it stayed consistently at 10.40.
10. Was it important for the researchers to include the total means and SDs for the study variables in Table 2 to promote the readers’ understanding of
the study results? Provide a rationale for your answer. a. Yes, this table helps to visualize the distribution of data. This visualization of means and standard deviations in this table were important to help demonstrate the study’s statistical results.
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