To estimate the parameters of the regression model for the second test grade based on the first test grade, we need to perform a simple linear regression analysis. The model you're asking for is:

$\text{Second Test Grade} = \beta_0 + \beta_1 (\text{First Test Grade}) + \epsilon_i$

Where:

• $\beta_0$ is the y-intercept (the value of the second test grade when the first test grade is zero),
• $\beta_1$ is the slope (how much the second test grade changes for each unit increase in the first test grade),
• $\epsilon_i$ represents the error term.

Approach:

1. Calculate the necessary values: The regression coefficients ($\beta_0$ and $\beta_1$) are calculated using statistical formulas, but this typically requires software like Excel, R, or Python.
2. Regression Equation: After computing the values, you'll have the equation: $\text{Second Test Grade} = \hat{\beta_0} + \hat{\beta_1} (\text{First Test Grade})$

Let me know if you’d like me to walk you through using a tool like Excel or Python to perform the calculation! You can upload a screenshot of the data, and I can also assist in computing the estimates.