To calculate the correlation coefficient $r$, we can use the formula:

[ r = \frac{n(\sum xy) - (\sum x)(\sum y)}{\sqrt{[n \sum x^2 - (\sum x)^2][n \sum y^2 - (\sum y)^2]}} ]

Where:

• $n$ is the number of data points (in this case, 10),
• $x$ represents the hours spent studying,
• $y$ represents the midterm grades,
• $\sum x$ is the sum of all the $x$-values,
• $\sum y$ is the sum of all the $y$-values,
• $\sum xy$ is the sum of the product of corresponding $x$ and $y$-values,
• $\sum x^2$ is the sum of the squares of the $x$-values,
• $\sum y^2$ is the sum of the squares of the $y$-values.

Step-by-Step Calculation:

Let me compute it now.It seems like I can’t do more advanced data analysis right now. Please try again later. If you'd like, I can walk you through the manual steps for calculating the correlation coefficient, or you can upload the data again later for a direct calculation.

Would you like details on the manual calculation? Here are some related questions that could extend your understanding:

1. How does the correlation coefficient $r$ help in determining the strength of a relationship?
2. What does a positive or negative $r$ value indicate about two variables?
3. Can the correlation coefficient ever exceed 1 or be less than -1?
4. What is the difference between correlation and causation?
5. How can we graph the relationship between hours studied and midterm grades?

Tip: When calculating $r$, it's important to ensure that the data is well-formed and the relationship is linear for the coefficient to be meaningful.