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In your research lab, you are conducting the Six Minute Walking Distance (6MWD) test, a significant predictor of longevity. The investigation involves understanding the relationship between the 6MWD test, age, and the level of nerve stimulation from an EMG test, loaded from the file file_name.csv. Perform the following correlation tests:

a) Conduct a Pearson's correlation of age and nervestim since they both follow a normal distribution. Output the rho and p-values as variables [rhoa, pvala].

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Final answer:

Calculate the Pearson's correlation coefficient and p-value for age and nervestim from EMG test scores to determine the strength and significance of their relationship, with rho indicating the correlation and a p-value less than 0.05 suggesting statistical significance.

Step-by-step explanation:

The Pearson's correlation requires that both variables follow a normal distribution. Assuming that age and nervestim metrics from EMG test scores follow this distribution, a Pearson's correlation coefficient (rho) and a p-value (pvala) can be calculated using appropriate statistical software or functions within a programming language that handles statistical analysis, such as Python's scipy.stats library or R's cor.test function.

The rho value would indicate the strength and direction of the relationship, with 1 being a perfect positive correlation, -1 being a perfect negative correlation, and 0 indicating no correlation. The p-value would test the null hypothesis that there is no correlation between the two variables, and a p-value less than 0.05 would typically be considered statistically significant.

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