Independent and Dependent Variable Analysis
Carrying out any analysis on independent and dependent variables in any set of data requires the understanding of what the two terms mean. On the one hand, dependent variable (usually abbreviated as DV) in statistics refers to a data element that depends on another data element. On the other hand, an independent variable (IV) is a data element on which the dependent variable depends. Such relation has an implication that a small change in the independent variable will have a significant change in the dependent variable. Notably, statistics helps researchers to understand the relationship that exists between dependent and independent variables. However, the interpretation of independent and dependent variables is determined by the nature of the statistical task: whether it is an observational study or an experiment.
It has been hypothesized that blood pressure in human beings is caused by high serum cholesterol. This paper will be based on the hypothesis that the level of serum cholesterol in human bodies and the blood pressure are positively correlated. In order to test the hypothesis, a study on the relationship between blood pressure and serum cholesterol was carried. The sample matrix included the following variables; smoking habits, degree of physical activity, triglycerides and glucose, non-fasting serum cholesterol, blood pressure, height and body weight. The paper seeks to find out the correlation between serum cholesterol levels and blood pressure.
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By the use of modified Student's test along with the use of non-adjusted crude method, the means were tested. However, Cohen, Cohen, West and Aiken (2003) point out that in order to have an analysis of the association of serum cholesterol, the nine factors should be studied. The factors addressed included socioeconomic status, physical activity, body mass, cigarettes smoked on a daily basis, age, serum glucose, serum triglycerides, diastolic blood pressure, and systolic blood pressure. The best method to use is the multiple regression method. The choice of such method was suitable, since it presents the researcher with the opportunity to analyze individual factors. However, in order to have the adjusted curves that clearly show an association of blood pressure and serum cholesterol, a linear regression method was adopted. The linear regression did not include the interaction effects of the risk factors mentioned above with serum cholesterol apart from blood pressure. In such way, an estimation of serum cholesterol was possible considering all the other factors except blood pressure.
Statistical and Theoretical Conclusions
For samples that had a high level of blood pressure, the cholesterol level was high and for samples that had a lower level of cholesterol, the blood pressure was low. Such results show a direct relationship between the level of cholesterol and blood pressure for the sample considered. The study carried by Bulpitt, Hodes and Everitt (1975), it showed that there was a correlation between serum cholesterol and systolic pressure as opposed to diastolic pressure. A possible explanation for such an observation is that in the process of ‘ageing’ or even during the formation of atheroma, the artery compliance greatly reduces, which increases systolic pressure.
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Research carried out by Gall, Gall and Borg (2006) has shown that correlation does not depend on the degree of screening. However, the study showed that there is a correlation between cholesterol and blood pressure. The variance of other risk factors such as triglycerides and body weight explain the relationship between cholesterol and blood pressure. From the foregoing, it is evident that the presence of high serum cholesterol dictates a high systolic blood pressure.
In any experimental or observational study, there are ethical issues that the researcher should put into consideration, especially in the process of data handling of the study (Gall et al., 2006). The aforementioned study involves an analysis of independent and dependent variables that are based on human beings. Thus, it is important to consider a number of ethical practices. To begin with, statistics insists on professionalism as far as respect for other people, self-respect, diligence, judgment and competence are concerned when presenting out any statistical findings (Cohen et al., 2003). In addition, it is ethical to acknowledge why the study was contacted as well as how the results will be useful to the participants of the study. In the case under analysis, the results that show the relationship between blood pressure and serum cholesterol can be used in the prediction of coronary heart diseases in human beings.