https://file.aiquickdraw.com/mathbot/file/17271977933028kyvro8e.xlsx

c. Develop a regression model to predict​ price-to-book-value ratio based on return on equity and growth.
ModifyingAbove Upper Y with caret Subscript iequals

enter your response hereplus

enter your response hereUpper X Subscript 1 iplus

enter your response hereUpper X Subscript 2 i
​(Round to four decimal places as​ needed.)

The dataset contains the following columns:

1. **Price/Book Value Ratio**: The target variable we need to predict.
2. **Return on Equity**: Independent variable \( X_1 \).
3. **Growth%**: Independent variable \( X_2 \).

I will now develop a regression model to predict the Price-to-Book Value Ratio using these two predictors. Let's calculate the coefficients and intercept of the regression equation.The regression model to predict the Price-to-Book Value Ratio (\( \hat{Y_i} \)) based on Return on Equity (\( X_{1i} \)) and Growth (\( X_{2i} \)) is given by the equation:

\[
\hat{Y_i} = 1.941 + 0.0598 \cdot X_{1i} + 0.022 \cdot X_{2i}
\]

This equation suggests:
- For each additional unit increase in Return on Equity, the Price-to-Book Value Ratio increases by approximately 0.0598 units, holding Growth constant.
- For each additional unit increase in Growth, the Price-to-Book Value Ratio increases by approximately 0.022 units, holding Return on Equity constant.

Would you like more details or have any questions about this model?

Here are 5 related questions to consider:
1. How accurate is this model in predicting Price-to-Book Value Ratio?
2. What is the R-squared value for this regression model?
3. Can we test the significance of each predictor variable?
4. How do we interpret the coefficients in a practical business context?
5. Are there any outliers or influential points that affect the model?

**Tip:** When interpreting regression coefficients, consider the scale and unit of each variable to understand their impact accurately.

Develop a regression model to predict price-to-book-value ratio based on return on equity and growth.

Learn how to develop a regression model to predict the price-to-book value ratio based on return on equity and growth. This tutorial covers key concepts like linear regression, coefficient interpretation, and model accuracy, using data-driven examples.

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