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The image contains a problem related to simple linear regression using sampled data. Let's break down what needs to be calculated based on the provided table and fields:

### **Table Details**
1. **Columns:**
   - Time since last eruption (\(x\), in hours)
   - Eruption height (\(y\), in meters)
   - The product (\(xy\)).

2. **You are required to calculate:**
   - \(n\): Sample size (the number of data points).
   - \(\sum x\): Sum of all \(x\) values.
   - \(\sum y\): Sum of all \(y\) values.
   - \(\sum x^2\): Sum of the squares of all \(x\) values.
   - \(\sum xy\): Sum of the products (\(xy\)).

3. **Regression Details:**
   - Sample correlation coefficient (\(r\)).
   - Slope (\(\beta_1\)).
   - \(y\)-intercept (\(\beta_0\)).

Would you like me to calculate these values step-by-step based on the data in the table?

The image contains a problem related to simple linear regression using sampled data. Let's break down what needs to be calculated based on the provided table and fields.

Learn how to calculate various statistics for simple linear regression using eruption data, including slope, intercept, and correlation coefficient. This problem covers key statistical concepts such as least squares regression and Pearson's correlation coefficient. Suitable for high school students in Grades 11-12.

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