Rank Correlation and Statistical Report

Abstract This study seeks to establish whether the relationship between the numbers of cigarettes smoked and the level of cotinine in the body is linear. Data of randomly selected subjects from National Health Examination Survey in the United States is the basis of this study. The methodology involves determining the strength of the relationship using Spearman’s rank correlation.Advertising We will write a custom essay sample on Rank Correlation and Statistical specifically for you for only $16.05 $11/page Learn More Data analysis is by use of SPSS, and the interpretation of the output of the analysis is given in the body of the paper under the analysis and result section. The researcher uses Wilcoxon’s Ranks test to verify the nature of the relationship between these variables. The null hypothesis of the study argues that the relationship between the concentration of cotinine in the body, and the number of cigarettes smoked is linear. On t he other hand, the alternative hypothesis argues that the relationship between the number of cigarettes smoked and the level of cotinine in the body is nonlinear. If the test statistic obtained is less than the level of significance (0.05), it means that the null hypothesis is not true and the researcher should reject it for the alternative hypothesis. This quest forms the essence of the study. Introduction Healthcare programs in the USA make provisions for the capitation of programs that facilitate collaborations between health insurers and clinical facilities to perform risk analysis of patients to help healthcare stakeholders determine the cost of care delivery (Ezzati, Lopez, Rodgers, Christopher, 2004). This report seeks to determine whether the rate of smoking correlates with risk of developing cancer by computing the concentration of cotinine in the body (Visweswara, 2007). The study uses values from randomly selected subjects in the National Health Examination Survey (Carve r Nash, 2009: Lehman Romano, 2005). This study seeks to determine whether there is a significant linear correlation between the number of cigarettes smoked and the level of cotinine in a smoker’s body. Data analysis and ResultsAdvertising Looking for essay on math statistics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Table 1. Test Statisticsb,c Y – X Z -2.981a Asymp. Sig. (2-tailed) .003 Monte Carlo Sig. (2-tailed) Sig. .000 95% Confidence Interval Lower Bound .000 Upper Bound .221 Monte Carlo Sig. (1-tailed) Sig. .000 95% Confidence Interval Lower Bound .000 Upper Bound .221 a. Based on negative ranks. b. Wilcoxon Signed Ranks Test c. Based on 12 sampled tables with starting seed 2000000. The mean number of cigarettes smoked per subject was 14.58, while the mean concentration of nicotine level in the body of a subject was 175.2050ng/ml. Wilcoxon’s ranks test was useful in determini ng the relationship between these two variables (Wickham, 2012). The null hypothesis to be tested argues that the relationship between the level of cotinine in a smoker’s body and the number of cigarettes smoked is linear (Watkins, Scheaffer, Cobb, 2010: DiClemente, Salazar, Crosby, 2013). Conclusion The test statistic obtained is less than the level of significance, which is approximately about 1.96. The results of the analysis reject the null hypothesis, while it verifies the alternative hypothesis (Lehman, 2005). The test statistic value, -2.981, is less than the level of significance. Hence, this result rejects the null hypothesis and supports the position that the numbers of cigarettes smoked do not determine the level of cotinine in the body and, thus, some factors external to this study are involved (Boyle, Gray, Henningfield, Seffrin, Zaton’ski, 2010: Weinberg Abramowitz, 2002: â€Å"Introduction to Hypothesis Testing,† 2006). This condition indicate s an opportunity for a research to investigate on the external factors that lead to an increase in the risk of cancer associated with cigarette smokers. References Boyle, P., Gray, N., Henningfield, J., Seffrin, J., Zatonski, W. A. (2010). Tobacco: Science, Policy and Public Health. Oxford : Oxford University Press. Carver, R. H., Nash, G. J. (2012). Doing Data Analysis with SPSS Version 18.0. Boston : Cengage Learning.Advertising We will write a custom essay sample on Rank Correlation and Statistical specifically for you for only $16.05 $11/page Learn More DiClemente, R. J., Salazar, L. F., Crosby, R. A. (2013). Health Behavior Theory for Public Health: Principles, Foundations, and Applications. Burlington, MA: Jones Bartlett Learning. Ezzati, M., Lopez, A. D., Rodgers, A. A., Christopher, F. J. (2004). Comparative Quantification of Health Risks: Global and Regional Burden of Disease. Geneva: World Health Organization. Introduction to Hypothesis T esting. (2006, July 13). Retrieved from sjsu: http://www.sjsu.edu/faculty/gerstman/StatPrimer/hyp-test.pdf Lehman, A. (2005). mp For Basic Univariate And Multivariate Statistics: A Step-by-step Guide. Chapel Hill: University of North Carolina. Lehman, E. L., Romano, J. P. (2005). Testing Statistcial Hypotheses. Berkeley: Springer. Visweswara, R. K. (2007). Bostatistics: A Manual of Statistical Methods for Use in Health, Nutrition and Anthropology. Delhi: K Visweswara Rao. Watkins, A. E., Scheaffer, R. L., Cobb, G. W. (2010). Statistics: From Data to Decision. John Wiley Sons. Inc: Hoboken.Advertising Looking for essay on math statistics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Weinberg, S. L., Abramowitz, S. K. (2008). Statistics Using SPSS: An Integrative Approach. Cambridge : Cambridge University Press. Wickham, C. (2012, October 17). Stat 411/511: Wilcoxon Rank Sum. Web. 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