...1. In comparing men and women, which group had higher body image scores? Provide a rationale for your answer. Women had higher body image scores with a X_73.07 compared to men with a X_60.22. With this study, the higher the mean, the greater the body image scores. Thus, the higher mean for women’s body image scores showed that women have stronger body image scores than men. 2. Men had higher variability in weight change over the last 12 months when compared to women. Is this statement true or false? Provide a rationale for your answer. True. SD indicates variability or spread of scores. Men had higher variability in scores with a SD 22.40 versus women with a SD 13.63. This shows that women had less variation in their weight over the 12 months than men did. Men often are more variable in their weight loss and gain, in this study. 3. What are the X_and SD values for men’s body weight ratio? X_53.66, SD 33.97. These values are found in Table 1. 4. Assuming that the distribution of scores is normal, calculate the scores where 95% of values around the mean lie for women with weight change over the last 3 months. Round your answer to two decimal places. Assuming that the distribution of scores is normal, 95% of women’s weight changes in the last 3 months were between (–12.88, 15.82). 5. Assuming that the distribution of body weight ratio is a normal curve, 95% of the men lie between which two values of body weight ratio around the mean? Round...
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...TermPaperWarehouse.com - Free Term Papers, Essays and Research Documents The Research Paper Factory JoinSearchBrowseSaved Papers Search over 100,000 Essays Home Page » Business and Management Exercise 36 Questions to Be Graded In: Business and Management Exercise 36 Questions to Be Graded EXERCISE 36 Questions to be graded 1. The researchers found a significant difference between the two groups (control and treatment) for change in mobility of the women with osteoarthritis (OA) over 12 weeks with the results of F(1, 22) = 9.619, p = 0.005. Discuss each aspect of these results. * The F-value suggests that there is a significant difference between the results of the control and treatment groups. The P-value of 0.005 is < the alpha of 0.05. This suggest that the groups are significantly different and the null hypothesis should be rejected. 2. State the null hypothesis for the Baird and Sands (2004) study that focuses on the effect of the GI with PMR treatment on patients’ mobility level. Should the null hypothesis be rejected for the difference between the two groups in change in mobility scores over 12 weeks? Provide a rationale for your answer. * Treatment group mean = control group mean * With the p-value being < the alpha, the null hypothesis would be rejected indicating the difference in the mean mobility scores. 3. The researchers stated that the participants in the intervention group reported a reduction in mobility difficulty at week...
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...DQ 1, Week 2 of HLT-362V Explain the importance of random sampling. What problems/limitations could prevent a truly random sampling and how can they be prevented? The importance of random sampling is the use of statistically derived random sampling processes. These ensure that survey results can be fortified as statistically illustrative of the population. Surveys that do not follow these procedures can yield results that lead to misguided market research, strategic, or policy decisions. Any survey in which no attempt is made to randomly select respondents, such as in polls, is likely to produce results that in no way reveal general public opinion. Even if many thousands of individuals participate. It is true that sampling randomly will eliminate systematic bias. The mathematical theorems which validate most frequent statistical procedures relate only to random samples. The problems/limitations that could prevent a truly random sampling are important because it assures that the conclusions you draw can be applied to your entire population. The subsequent issues that could cause problems with random sampling are if the experimenter selects a sample that is too small and the experimenter does not understand the population. This can be prevented by using the standard deviation which, is divided by the square-root of the sample number (n), which means that the standard error will be smaller than the population standard deviation, and that it will get progressively smaller as...
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...Name: Lincy Nedumackal Class: HLT-362V Due Date: 12/22/13 STUDY QUESTIONS 1. The sample size was 392 (N = 392) as indicated in the “Introduction.” 2. In Table 1, the c² = 6.45 for the Race of Child. 3). Four null hypotheses were accepted since four c² values were not significant, as indicated in Table 1. No significant results indicate that the null hypotheses are supported or accepted as an accurate reflection of the results of the study. 4. The c² = 21.95 for Marital Status (%): Married/living with partner or Living alone. The symbol next to this c² value indicates that it is statistically significant at p ≤ .001. If alpha (α) = 0.05 for this study, then p is less than α indicates that the c² value is statistically signifi cant. 5. No, p ≤ .001 has a greater significance than p ≤ .05, since the smaller the p value, the more significant the findings. Thus, p ≤ .05 is not as significant as at p ≤ .001. 6. Mean household income has a greater statistically significant value because it is reported significant at p ≤ .001, whereas Education (of adult) is reported significant at p ≤ .05. The smaller the p value, the more significant the findings. 7. Yes, Mean household income is also significant at p ≤ .05, since p ≤ .001 has a greater significance than p ≤ .05. What is significant at p ≤ .001 is also significant at p ≤ .05. 8). There is no difference in Mean household income among the three groups determined by levels of insurance (uninsured, Medicaid-enrolled...
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...HLT 362V Exercise 36 Questions to be graded 1-10 1. The researchers found a significant difference between the two groups (control and treatment) for change in mobility of the women with osteoarthritis (OA) over 12 weeks with the results of F ₍₁‚ ₂₂₎ = 9.619, p=0.005. Discuss each aspect of these results. Answer: The F value at 5% level of significance shows a significant difference between the control and the treatment groups. Therefore, the null hypothesis should be rejected because the p value 0.005 is less than 0.05 which means that the control and the treatment groups are different. 2. State the null hypothesis for the Baird and Sands (2004) study that focuses on the effect of the GI PMR treatment on the patients’ mobility level. Should the null hypotheses be rejected for the difference the two groups in change in mobility scores over 12 weeks? Provide a rationale for your answer. Answer: The null hypothesis would be that the means between the two groups, the control group and the treatment group will be equal. Since the p value is 0.005 0.01, the result is not statistically significant. Therefore, I would accept the null hypothesis because there is no difference between the control group and the treatment group. 6. Can ANOVA be used to test proposed relationship or predicted correlations between variables in a single group? Provide a rationale for your answer. Answer: No. ANOVA cannot be used to test proposed relationship or predicted correlations...
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...Running head: STATISTICS. EXERCISE 16 1 STATISTICS. EXERCISE 16 SUMITHA THOMAS GRAND CANYON UNIVERSITY STATISTICS. EXERCISE 16 STATISTICS. EXERCISE 16 Name: Sumitha K Thomas Date:3/3/13 Class : HLT -362V 2 1) The researchers analyzed the data they collected as though it were at what level of measurement? a) Nominal b) Ordinal c) Interval/ration d) Experimental The correct answer is: d)experimental. 2) What was the mean post test empowerment score for the control group? Answer: 97.12 3) Compare the mean baseline post test depression scores of the experimental group. Was this an expected findings? Provide a rational for your answer? Answer: The baseline score of the experimental group is 14.00. According to the data provided in exercises 16, the depression decreased to 13.36 after the empowerment program. This is a positive result, which shows slight improvement (0.64). 4) Compare the mean baseline and posttest depression scores of the control group. Do these scores strengthen or weaken validity of the research results? Provide a rationale for your answer? Answer: The mean baseline depression scores of control group is 10.40. The mean post test depression scores of control group 10.40. Because the scores remains same STATISTICS. EXERCISE 16 at the baseline level and post test level of depression rate of control group is neither weaken or strengthen with empowerment program, which shows no improvement with the program but also their depression score doesn’t increase...
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...Lindsey Pierce Exercise 11 HLT-362V January 14, 2016 Using Statistics to Describe a Study Sample 1. What demographic variables were measured at least at the interval level of measurement? Answer: The demographic variables that are measured at the interval level are: age, income, length of labor, return to work, and number of hours working per week. 2. What statistics were used to describe the length of labor in this study? Were these appropriate? Answer: The statistics used to describe the length of labor in this study were mean and standard deviation. These were appropriate as they both can be calculated at the interval level of measurement. 3. What other statistic could have been used to describe the length of labor? Provide a rationale for you answer. Answer: The median could be used though the mean and standard deviation are closer for both of the groups. 4. Were the distributions of scores similar for the experimental and control groups for the length of labor? Provide rationale for your answer. Answer: Yes, the standard deviation measured the average deviation values of the mean. So, the difference between the two groups would be 0.48 hours which in this case is less than 30 minutes so the mean had a difference of 1.84 hours. 5. Were the experimental and control groups similar in their type of feeding? Provide a rationale for your answer. Answer: Yes, both of the groups were similar in their type of feeding though the difference in...
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...Geraldo Gutierrez Gomez Grand Canyon University HLT-362V September 6, 2015 Professor: Steve Austin Workbook Exercise 11 to 16 Statistics Class 1. What demographics variables were measured at least at interval level measurement? The demographics variables measured at least on the interval level measurement were the number of hours per week and length of labor hours. 2. What statistics were used to describe the length of labor in this study? Where these appropriate? The mean and standard deviation were used to describe the length of labor of for both group the control and experimental group. I agree these were appropriate measures of statistics. 3. What other statistics could have been used to describe the length of labor? Provide rationale for your answer. In my opinion in addition to the mean and standard deviation, the mode could be used in this study to also describe the length of labor. It will give us and idea of how long the common length of labor was. The median could also been used, but in my opinion will not be more beneficial to knowing the average and the most common length of hours on the control and experimental groups. 4. Were the distributions of scores similar for the experimental and control groups for the length of labor? Provide rationale for your answer. The standard deviation for the experimental group was 7.78(length of hours) and for the control group was 7.2(length of hours).By looking at the scores of the standard deviation my opinion...
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