https://file.aiquickdraw.com/mathbot/file/1727196228280aioyx1x6.xlsx

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

enter your response hereplus

enter your response hereUpper X Subscript 1 i
​(Round to four decimal places as​ needed.)

The dataset consists of three columns: 

1. **Price/Book Value Ratio**
2. **Return on Equity**
3. **Growth%**

To develop the regression model that predicts the **Price/Book Value Ratio** based on the **Return on Equity**, we will fit a simple linear regression model. I will proceed with the regression and round the coefficients to four decimal places.The linear regression model to predict the **Price-to-Book Value Ratio** based on **Return on Equity** is:

\[
\hat{Y}_i = 2.3328 + 0.0700 X_{1i}
\]

Where:
- \(\hat{Y}_i\) is the predicted **Price-to-Book Value Ratio**.
- \(X_{1i}\) is the **Return on Equity**.

Would you like further details on the regression analysis, or do you have any questions?

Here are 5 related questions for deeper exploration:
1. How does the model's accuracy compare to other possible predictors?
2. Can we add the **Growth%** variable to improve the model's performance?
3. How do we interpret the coefficient of the model in practical terms?
4. What assumptions are we making when using linear regression here?
5. Can we use this model for future predictions if new data is available?

**Tip:** Always check the residuals of the model to ensure that the linearity assumption holds.

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

This page covers how to develop a linear regression model to predict the price-to-book-value ratio based on return on equity. The dataset includes variables like Price/Book Value Ratio, Return on Equity, and Growth%. The resulting model uses Return on Equity as the predictor.

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