Childhood Obesity Interventions: Data Analysis

Data Analysis Plan for Demographic Variables

Demographic characteristics of the sample are critical for research, and they need to be described as the first step of data analysis. Demographic variables for this study include children’s age, gender, and race. Additionally, taking into consideration the fact that the proposed research is mainly focused on the use of parental education to overcome obesity, it seems to be advantageous to identify if a child is raised in a single-parent family or has two parents. Their economic conditions should also be considered because they affect eating habits and lifestyles (Simpson, 2015).

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The first step of the data analysis plan will be to conduct the univariate analysis for demographic information using the quantitative approach. It is important to determine the mean, median, frequency distribution, and standard deviation. The mean will be identified to reveal general information about the sample and demographic characteristics of the involved children. The median will be revealed with the help of the division of the sample into two groups. The standard deviation will help determine the lowest and the highest values for each variable category. To summarize descriptive data related to the participants of this research, it is appropriate to use tables and bar graphs that will make it easier to compare data associated with different variables and participants.

Data Analysis Plan for Study Variables

For this study, it is important to conduct descriptive and inferential statistical tests. Descriptive data will be measured with the help of identifying the mean, the standard deviation, and the frequency distribution for the number of hours that parents devote to their education regarding childhood obesity and differences in children’s body mass index (BMI). The arithmetic average of each variable will be calculated. These data will provide the background for further examining the relationships between the study variables.

Inferential statistical tests will include a series of unpaired t-tests that provide an opportunity to compare two groups: children whose parents received education and children who received only medical treatment. It will be possible to reveal whether there is any difference in their weight changes and obesity rates. Thus, it will be possible to reveal what intervention is more or less effective. The described analysis of research variables will make it possible to test the research and null hypotheses and contribute to the treatment of obesity in children.

References

Simpson, S. (2015). Creating a data analysis plan: What to consider when choosing statistics for a study. The Canadian Journal of Hospital Pharmacy, 68(4), 311-317.

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StudyCorgi. (2021, July 8). Childhood Obesity Interventions: Data Analysis. Retrieved from https://studycorgi.com/childhood-obesity-interventions-data-analysis/

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"Childhood Obesity Interventions: Data Analysis." StudyCorgi, 8 July 2021, studycorgi.com/childhood-obesity-interventions-data-analysis/.

1. StudyCorgi. "Childhood Obesity Interventions: Data Analysis." July 8, 2021. https://studycorgi.com/childhood-obesity-interventions-data-analysis/.


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StudyCorgi. "Childhood Obesity Interventions: Data Analysis." July 8, 2021. https://studycorgi.com/childhood-obesity-interventions-data-analysis/.

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StudyCorgi. 2021. "Childhood Obesity Interventions: Data Analysis." July 8, 2021. https://studycorgi.com/childhood-obesity-interventions-data-analysis/.

References

StudyCorgi. (2021) 'Childhood Obesity Interventions: Data Analysis'. 8 July.

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