IHP 525 Milestone Three Table For This Milestone In Order To ✓ Solved

Ihp 525 Milestone Three Tablefor This Milestone In Order To Explore Y

For this milestone, in order to explore your health question you are investigating, you need to plan what descriptive statistics and statistical test you will need to run, as well as what graph you will need to create. Step 1: Complete the table below in which you will propose the calculations and graph(s) you will need to perform to answer the health question you are investigating. Question: Answer: What is your health (research) question? What is the corresponding null and alternative hypotheses? List the descriptive statistics you will compute, using which variable(s), to help answer your health question.

What is the name of the statistical test that you will use to test your hypothesis and answer your health question? What is the formula for your chosen statistical test? Why is the statistical test you chose appropriate to answer your health question? Be sure to be clear on how the two variables you described in Milestone Two are used to complete this test. Which graph(s) (histogram, stem and leaf, boxplot, bar graph, scatterplot) will you use to visualize the answer to your health question? Be specific and include which variables will be used and if the graph will be created for different subgroups of subjects.

Step 2: Provide a 1-2 paragraph explanation below as to why you chose the calculations outlined in the table above to explore your health question. Describe what statistics you will compute in order to answer your chosen health (research) question. Be sure to discuss any graphs that you will compute and what information they will provide to help you answer your health question.

Sample Paper For Above instruction

Introduction and research question: The purpose of this study is to investigate the relationship between physical activity levels and blood pressure among adults aged 30-50. The research question posed is: "Is there a significant difference in blood pressure between individuals with high and low physical activity levels?"

Null and Alternative Hypotheses: The null hypothesis (H0) states that there is no difference in blood pressure between individuals with high and low physical activity levels. The alternative hypothesis (H1) asserts that there is a significant difference in blood pressure between these two groups.

Descriptive Statistics: To explore this question, I will calculate the mean, median, and standard deviation of blood pressure readings within each physical activity group. Additionally, I will determine the frequency distribution of activity levels to categorize participants into high and low groups effectively.

Statistical Test Selection: A two-sample independent t-test will be used to compare the mean blood pressure between the high and low activity groups. The formula for the t-test is:

t = (M1 - M2) / √[(s1²/n1) + (s2²/n2)]

This test is appropriate because it compares the means of two independent groups, assuming normal distribution and equal variances, which will be verified beforehand. The two variables involved are the physical activity level (independent variable, categorical) and blood pressure (dependent variable, continuous).

Graphical Visualization: To visually explore the data, I will create boxplots for blood pressure across the two groups to observe distribution and potential outliers. Additionally, a scatterplot with overlaid means will be used to compare blood pressure readings between groups, possibly segmented by age or gender subgroups for more detailed insights.

Explanation of Chosen Calculations and Visualization: The descriptive statistics will provide central tendency and dispersion measures to understand the blood pressure distribution within each physical activity group. The t-test enables testing the hypothesis of no difference in mean blood pressure between the groups, providing a statistical basis for inference. The boxplots will visually reveal overlap, skewness, and outliers in blood pressure readings, offering intuitive confirmation of the statistical test results.

References

  • Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage Publications.
  • Gravetter, F. J., & Wallnau, L. B. (2016). Statistics for The Behavioral Sciences. Cengage Learning.
  • Motulsky, H. (2014). Intuitive Biostatistics. Oxford University Press.
  • Pagano, R. R., & Gauvreau, K. (2000). Principles of Biostatistics. Duxbury Press.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics. Pearson.
  • McHugh, M. L. (2012). The Chi-Square Test of Independence. Biochemia Medica, 22(2), 277-282.
  • Yates, D. (2004). An Introduction to Statistical Methods in Epidemiology. Oxford University Press.
  • Wilkinson, L., & Task Force on Statistical Inference. (1999). Statistical Methods in Psychology Journals: Guidelines and Explanations. American Psychologist, 54(8), 594–604.
  • Lehmann, E. L., & Romano, J. P. (2005). Testing Statistical Hypotheses. Springer.
  • Hocking, R. R. (2003). Methods and Applications of Linear Regression. John Wiley & Sons.

Related Assignments