The data includes three columns:

1. Price-to-Book Value Ratio (dependent variable, $Y$)
2. Return on Equity (independent variable $X_1$)
3. Growth Percentage (independent variable $X_2$, not used in this part of the question)

Now, let's develop a simple linear regression model where the Price-to-Book Value Ratio is predicted based on Return on Equity ($X_1$).

The regression model will be in the form: $\hat{Y}_i = \beta_0 + \beta_1 X_{1i}$ We'll compute the coefficients $\beta_0$ and $\beta_1$.The regression model to predict the Price-to-Book Value Ratio ($Y$) based on Return on Equity ($X_1$) is:

$\hat{Y}_i = 2.3197 + 0.0706 X_{1i}$

Where:

• $2.3197$ is the intercept ($\beta_0$).
• $0.0706$ is the slope coefficient for Return on Equity ($\beta_1$).

Let me know if you'd like further details or have any questions.

Here are some follow-up questions:

1. How do we interpret the slope in this context?
2. What is the coefficient of determination ($R^2$) for this model?
3. How would you extend the model to include Growth Percentage ($X_2$)?
4. What assumptions are made in linear regression?
5. How can we test the significance of the coefficients?

Tip: The slope tells you how much the Price-to-Book Value Ratio is expected to change for a one-unit increase in Return on Equity.