Correlation and regression are statistical tools for describing the nature and strength of a linear association between two continuous variables. However, even when a strong association is found, causation cannot be inferred.
To prepare for this Application Assignment read the Lin article, “Inverse Correlation Between Heart Rate Recovery and Metabolic Risks in Healthy Children and Adolescents” from this week’s Learning Resources.
To complete this Application Assignment, a paper that addresses the following:
- Select a data table from the article that best describes the use of the correlation and regression statistic.
- Identify and interpret the correlation coefficient and coefficient of determination in the data table.
- Do you believe this was the best way to present the data?
- Interpret the statement, “Correlation is not causation” and how it applies to this article.
Inverse Correlation Statistics
The data table, which we have selected for this assignment, is Table-3. It is the table, which presents a person correlation test. Correlation is similar to regression; however, regression is more detailed and reveals whether the relationship is significant or not. Also, we can also use various kinds of tests, such as Durban Watson Test, to learn whether the applied statistical test is valid or not.
Both correlation and regression tests reveal the nature of the relationship between two variables. However, correlation does not have a dependent variable, whereas in regression tests, there must be a dependent variable. In this study, Pearson Correlation has been used, which reveals the nature of the relationship between different variables. We know that the collected data has been split into two groups, boys, and girls, which provide a more comprehensive understanding regarding the data and results that were obtained from applying a statistical test.
The selected variables 1) Waist Circumference, 2) Systolic Blood Pressure, 3) Diastolic Blood Pressure, 4) Triglycerides, 5) Glucose, 6) HDL and 7) Log-CRP. In the study, these variables have been Heart Rate Recovery. The data about each variable has been collected in three intervals (after every one minute of exercise).
Waist Circumference has a negative correlation of 10.5% after 1 minute of exercise. However, the correlation between Heart Recovery and Waist Circumference increases to -33.9% after 2 minutes of exercise. After three minutes of exercise, the correlation between the boys’ Waist Circumference and Heart Recovery is -27%. All the results are significant, as the P-value is below 0.05.
The correlation results (for girls), between Waist Circumference and Heart Rate Recovery, are slightly different. For instance, after 1 minute of exercise, the Waist Circumference is -7% correlated with Heart Recovery. After two minutes of exercise, the correlation between the two variables is -30%, and after three minutes it is -35%.
The data has been presented in a very comprehensible manner, which makes it quite easy for the reader to understand the direction of the relation and the strength of relationships (Lin, et al., 2008).
Reference
Lin, L. Y., Kuo, H. K., Lai, L. P., Lin, J. L., Tseng, C. D., & Hwang, J. J. (2008). Inverse Correlation Between Heart Rate Recovery and Metabolic Risks in Healthy Children and Adolescents. Diabetes Care, 31(5), 1015-1020.
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