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Biological & Biomedical Sciences
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Course: BIO500. Rank Correlation. Biological & Biomedical Sciences Essay

Essay Instructions:

For the following assignment, use the Rank Correlation that was demonstrated in Chapter 12 of the textbook (page 566). Utilizing Excel or SPSS:
Use a rank correlation coefficient to test for a correlation between two variables.
Use a significance level of α=0.05. Write a 500 word lab report explaining your findings. As well as show an excel document or SPSS
The new health care program in the United States makes provisions for capitation programs where health care insurers work with clinical facilities to perform risk analysis of patients to determine the cost of providing care. The following assignment might be used to assess how much a person smokes.
When nicotine is absorbed by the body, cotinine is produced. A measurement of cotinine in the body is therefore a good indicator of how much a person smokes. The reported number of cigarettes smoked per day and the measured amounts of cotinine (in ng/ml) are provided. (The values are from randomly selected subjects in a National Health Examination Survey.) Is there a significant linear correlation? How would you measure the cotinine level in the body? Explain the result.
Refer to the "Rank Correlation Table."
APA format is not required, but solid academic writing is expected.
You are not required to submit this assignment to Turnitin.

Essay Sample Content Preview:

Rank Correlation
Name
Course: BIO500
Date  The Spearman rank correlation coefficient (rho) is 0.624, the 2-tailed p-value is 0.0301, S-statistic: 107.53, while the Pearson correlation coefficient (Multiple R) is 0.262 and p-value is 0.411. In the rank correlation, there are ties in the ranks for 10 and 20 (cigarettes per day) where the exact p-value is not calculated, but rather approximated based on the sample. Spearman correlation analysis is a nonparametric statistical test to determine the association between two quantitative variables. In this case, cotinine (y) is the dependent variable or outcome and a cigarette per day (x) is the independent variable.  
The rank correlation test is a good alternative to the Pearson correlation test since it has almost the same power, and is based on the range of values.  The calculation of the rank correlation coefficient is based on ranking the variables from the largest the smallest and calculating the differences.  Judging the relationship between the two variables depends on the correlation coefficient after ranking and ordering the variables.   However, even if there is a relationship between variables, this does not imply causality (Triola, 2015). 
When using the rank correlation coefficient, the p-value is 0.0301, and the result is significant at p < 0.05, and there is a significant linear correlation.   The numerator is six multiplied by the sum of square differences, while the denominator is the sample size power three minus the sample size (123-12).  In rank correlation, there may be values that are repeated, and that affects the calculation of the Spearman correlation, but corrections are made so that the ties do not affect the calculations (Huck, 20...
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