Step 1 :Given the data points, we have the following values: \(x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\) and \(y = [0.1, 0.7, 1.1, 2.1, 2.9, 3.1, 3.1, 4.4, 4.6, 5.1]\).
Step 2 :The number of pairs of data, denoted as \(n\), is 10.
Step 3 :The sum of the x-values, denoted as \(\sum x\), is 55.
Step 4 :The sum of the y-values, denoted as \(\sum y\), is approximately 27.2.
Step 5 :The sum of the product of the x and y values, denoted as \(\sum xy\), is 195.6.
Step 6 :The sum of the squares of the x-values, denoted as \(\sum x^2\), is 385.
Step 7 :The sum of the squares of the y-values, denoted as \(\sum y^2\), is approximately 100.28.
Step 8 :Substitute these values into the formula for the correlation coefficient, \(r = \frac{n(\sum xy) - (\sum x)(\sum y)}{\sqrt{[n\sum x^2 - (\sum x)^2][n\sum y^2 - (\sum y)^2]}}\).
Step 9 :After calculating, we find that the correlation coefficient, \(r\), is approximately 0.987611212433532.
Step 10 :Rounding to the nearest thousandth, the final answer is \(\boxed{0.988}\).