What is the null hypothesis? What is the research hypothesis? There is no relationship between income and obesity. There is a relationship between income and obesity. Describe your sampling method. What is your sample size? Who is your population of interest? How representative is the sample of the population under study? In order to attain patient information, in an orderly form, that was reliable and accurate, we partnered with Health and Human Services (DHHS) offices around the Country. We randomly selected 100 DHHS offices, distributed correspondence explaining the purpose of our research and requested data from 20 randomly chosen health care applications completed by men from each of them. Due to protected health information being involved, we had to ensure that the transaction was HIPAA approved and did not disclose any personal information about an individual. In order to do so, the correspondence asked that the DHHS offices only send the following details in matched pairs (monthly income, weight). The sample size would be 100 DHHS offices x 20 applications = 2,000 pairs of data (income, weight). The population of interest is Medicaid applicants since income is a factor in whether or not they receive assistance and income is a requirement on the application. Although weight is not identified on the Medicaid application, we are assuming for the sake of this study that the DHHS office has weight in the patient record. Therefore we can receive all of our data from the same type of source, public health offices, who can each provide a list of 20 sets of data. I think the population under study is a great sample to examine. Medicaid recipients are often required to get a primary care provider (PCP) and are incentivized to utilize the PCP. The PCP would be the first point of contact for a yearly physical to address any serious health issues, such as obesity. The data needed to be selected with the same sex. For example, if the data were collected from men and women, but the sex was not identified, the data may be skewed because the range of weights would be very large. Since we requested records from all men, we expect more consistency in the research. They also are required to re-apply each month to make sure they still qualify based on income. The elicited data should be relatively recent. Describe the statistical analysis. The statistical analysis that was conducted was a correlation study. The data were collected using an appropriate method, a scatterplot of the data sets confirmed a linear relationship, and any outliers were removed. In this case, the data sets were plotted and showed a negative correlation, indicating that the higher the income, the lower the weight. A negative correlation resulted in a correlation coefficient of r = -0.357. What is your IV? DV? What level of measurement are your IV and DV (nominal, ordinal, interval or ratio?) The independent variable is the monthly income amount. The dependent variable is the weight. The level of measurement for the IV and DV are both ratio. Although the data closely resembles interval, they have a starting point at zero. The data sets can be arranged in order, the differences are meaningful and they have a natural starting point of zero (Triola, 2014, p. 20). What is your alpha level? I selected an alpha level of 0.05. Did you reject the null hypothesis? Yes, I rejected the null hypothesis that stated there is no relationship between income and obesity. What information did you use to lead you to your conclusion? I used the alpha value of 0.05 and the p-value of .0218 to develop my conclusion. Was your p-value greater than or less than your alpha? The p-value was less than alpha, therefore, I rejected the null hypothesis because there is sufficient data to provide evidence that income and obesity are correlated.
