MINI-STUDY PART 1 2

Mini-Study Part 1

1. State your topic
   The relationship between obesity and overweight and diabetes among diabetic patients (25 years
   and above)
2. Who is the population for your claim? Justify your statement.
   The population being studied is diabetic adults aged 25 years and older. Evidence has linked
   obesity and overweight with the onset of type-2 diabetes – a condition characterized by elevated
   blood glucose (sugar) levels. Obesity and overweight are among the many risk factors (CDC,
   2020). Obesity is a serious health condition associated with sleep disorders, cancers, high blood
   cholesterol, heart disease, atherosclerosis, hypertension, and metabolic syndrome.
3. What question(s) will you ask in your survey to gather data on your claim? Explain
   the rationale for each question.
   Question: What is the relationship between obesity and overweight and diabetes?
   This relationship-based question can help describe the trend and correlation between two or more
   variables within the selected demographic group (diabetic adult patients). Relationship-based
   questions are commonly used in quantitative research to collect numerical data that would later
   be used to define the interaction, trend, association, and relationship between independent
   variables and dependent variables (Megele, 2015).
4. What variables will be in your study? What type of variable are they (ordinal,
   nominal, discrete, continuous, etc.)?
   The independent variables include obesity and overweight, while the dependent variable is
   diabetes. All these variables can be described as continuous because they can be measured on a

MINI-STUDY PART 1 3
scale, and it is possible to measure these variables’ variance, standard deviation, median, and
mean (Smithson & Merkle, 2013).

5. Where will you post your survey, and how will it reach your target population?
   (Facebook, email, in person, etc.)?
   I will survey via email. Eligible diabetes patients will be identified through purposeful sampling.
   Uniform survey questions will then be emailed to all participants.
6. How will you collect your data? (Survey Monkey, Facebook Question, by
   Hand/Excel, etc.)
   Survey Monkey will be the primary method for data collection.
7. What type of sampling method will you use? Justify your choice and cite a reference
   supporting your decision.
   Purposeful sampling will be used to identify diabetic patients to participate in the research.
   Purposeful sampling is necessary to ensure that the right participants with the required
   characteristics are recruited for the study, such as diabetic patients without other underlying
   conditions like heart disease (Palinkas et al., 2015).
8. What two types of graphs that you have learned about are the most appropriate for
   your data? Justify your statement and cite a reference supporting your decision.
   Simple bar graphs and scatter plots are the two most appropriate graphs for the data (Navidi &
   Monk, 2012). Simple bar graphs are appropriate in providing graphical summaries of descriptive
   statistical relationships, such as percentages of dependent variables (diabetes) vs independent
   variables (overweight and obesity). On the other hand, a scatterplot will provide an excellent
   graphical presentation and summary for bivariate data (datasets consisting of ordered pairs). For

MINI-STUDY PART 1 4
example, the scatterplot will provide a graphical summary of the relationship between large
volumes of diabetes datasets vs overweight and obesity.

9. What eight descriptive statistics that you have learned about are the most
   appropriate for your data? Justify your statement and cite a reference supporting
   your decision. HINT: think about if the data has outliers, is quantitative, is
   categorical vs interval, etc.
   The eight descriptive statistics that are most appropriate for the study include measures of central
   tendency (count, percent, and frequency), measures of central tendency (mode, median, and
   mean), and measures of variation and dispersions (standard deviation and variance). These
   metrics will help in characterizing data based on their respective properties or features. For
   example, standard deviation and variance can help find the difference between the mean and
   observed scores (Longest, 2014).

MINI-STUDY PART 1 5

References
CDC. (2020). The health effects of overweight & obesity.
https://www.cdc.gov/healthyweight/effects/index.html
Longest, K. C. (2014). Using Stata for quantitative analysis. SAGE Publications.
Megele, C. (2015). Psychological and relationship-based practice. Critical Publishing.
Navidi, W. C., & Monk, B. J. (2012). Elementary statistics. McGraw-Hill.
Palinkas, L. A., et al. (2015). Purposeful sampling for qualitative data collection and analysis in
mixed method implementation research. Administration Policy in Mental Health, 42(5),
533-544. doi: 10.1007/s10488-013-0528-y
Smithson, M., & Merkle, E. C. (2013). Generalized linear models for categorical and continuous
limited dependent variables. CRC Press.