Correlation Statistics, Essay Example

The table analyzed for the determination of correlation statistics application in the study by Lian-Yu Lin (et, al, 2002) entitled Inverse Correlation Between Heart Rate Recovery and Metabolic Risks in Healthy Children and Adolescents is table 3 which is noted as the Age Adjusted Correlation Coefficients between HRR Parameters and Other Variables. This table presentation found atpage 1017 practically shows a variable-dependent figure on how the different health elements implement a sense of effect on the current health status of the participants observed for the study.

The comparison shown in the table does create a distinct impact on how the participants have common and differing grounds between each other as well as how the elements surrounding their current health state further affects the overall health condition they are dealing with. Through the conversion of the metabolic factors examined in the study, the researchers were able to find out that there are specific differences and points of grounded implications on how each component affect the health of the patient depending on his or her gender.

In a way, since the study is based on a quantitative pattern of study, the presentation used to define the elements noted in the research is valid and practically designed to provide the right information needed for the completion of the task being completed and the hypothesis being proven. The numerical data that is used to give a determinable pattern of identifiable development as part of the factual background that surrounds the study implicates a better sense of what is noted as the point of extensive and solid comparison.

Conveying a message based on logical distinction shall provide the readers with a much better perception of the truth that the research aims to present to the public. The point of correlation shown between results among the participants [based on gender differences] receives an average of .08 and .06 accordingly which suggests that the coefficient between the said elements is strong enough to identify with the contrasting factors used to identify with the research being pursued.

When it comes to the contrasting elements surrounding the factors involved in the study, it is important to note what has been pointed out at one part of the research which insists that:

Whatever the correlation pattern between metabolic risks and the autonomic nervous system is different in the sympathetic and parasympathetic nervous system need further study to clarify (1018).

As seen from this point of distinction, the elimination of marginal mistakes has been pointed out in the discussion as somewhat the conditional point of comparison between the elements examined among the participants as they handle a definite post of observation and distinct analysis by the researchers. The documentation and the relative concept of determination on how distinct elements of health variables create a distinct determination on how the situation of the participants are determined by both external and internal factors directly defining their health status.

This could be connected to what is shown in table 4 known as the Standardized Correlation Coefficients and Values of Multiple Linear Regression Analysis by using HRR as Dependent Variables and other Parameters as Independent Variables. In relation to the results shown in Table 3, the notification on how the rate of metabolism affects the overall capacity of the patient to respond to medication and acquire better course of health-advancement entails to create a distinct insistence on the overall result of the study. Practically, metabolism rate has also been reconnected to the age of the participants. And as shown through the regression table, the age-range [to which the participants belong] affects the metabolism rate in parallel. This then mandates the fact that as the patient grows older, metabolism rate slows down, hence affecting faster effect of the medication on the body’s overall system. Consequently, these results suggests on how the recommendation for increased physical activity is valued especially for the improvement of medicine intake of the patients.

In relation to this, it could be said that even though there are matters of comparison specifically determined to provide a practical definition on how factors of development and health operations affect individuals with supposedly good health status, it cannot be said that the results taken from the research and the correlation approach used to analyze the data collected for the study would identify well on what caused the changes. Lin Walden’s study further imposes on how such factors, including the parallel connection between age and gender actually co-affect each other especially in terms of influencing how the body responds to medications and therapies that are imposed on patients with metabolic anomalies. The variables used in the study are not only mere representations of factorial effects that show how both age and gender differ in terms of nutrient production and consumption among patients. Instead, they are treated as determinable factors that are expected to make a defining constant that allows readers and other audiences to become more effective in interpreting the data for themselves and finding an implicative factor that would make these elements more useful for practical application.  In short, the study points out [as seen from both tables 3 and 4] that metabolic rate functions fully to provide a definite term of development in terms of mandating a sense of improvement on how health anomalies such as diabetes [and other similar ailments] could be treated through physical therapy based on the gender and the age of the patients being assisted for recovery and health support operations.

References

Everitt, B. S. (2002). Cambridge Dictionary of Statistics (2nd ed.). CUP.

Glantz, Stanton A.; Slinker, B. K. (1990). Primer of Applied Regression and Analysis of Variance. McGraw-Hill.