Final answer:
Without the actual data for milk output and calcium rations, we cannot compute the Pearson correlation. However, we understand that this coefficient measures the strength of the relationship between two variables and that interpretation of its value alongside p-values helps in assessing statistical significance.
Step-by-step explanation:
To calculate the Pearson correlation between the output of milk and the calcium ration, you would typically use the formula for the Pearson correlation coefficient (r), which is computed as the covariance of the two variables (milk output and calcium ration) divided by the product of their standard deviations. However, without the actual data provided (the values for milk output and calcium rations), it's not possible to compute the exact correlation coefficient here. Still, the unexplained variability in milk output being 16% suggests that there's a considerable amount of variation in milk output that is not explained by the calcium boluses. The closer the value of r to 1 or -1, the stronger the correlation, while a value of 0 indicates no correlation.
Interpretation of results such as p-values, like the provided '0.0118', would help in determining the statistical significance of the correlation. If you had specific numerical data, you could use software or statistical tools to calculate r and then compare it to the critical value to assess significance.