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Following is information on the price per share and the dividend for a sample of 30 companies. Calculate the regression equation that predicts price per share based on the annual dividend. (Round your answers to 4 decimal places.) Price =		+		dividend


The regression equation that predicts the price per share (\( P \)) based on the annual dividend (\( D \)) is:

\[
P = 28.9367 + 2.4050 \times D
\]

Where:
- \( P \) is the predicted price per share.
- \( D \) is the annual dividend.

Let me know if you would like further details or have any questions!

Here are 5 related questions:
1. How is the goodness of fit (R-squared value) of the regression model calculated?
2. What does the slope (2.4050) indicate in the context of this model?
3. Can we interpret the intercept (28.9367) economically?
4. How would we test the significance of the regression model?
5. What would be the predicted price for a company with an annual dividend of 15?

**Tip**: In linear regression, a higher R-squared value means that the independent variable explains more of the variance in the dependent variable.

Following is information on the price per share and the dividend for a sample of 30 companies. Calculate the regression equation that predicts price per share based on the annual dividend. (Round your answers to 4 decimal places.)

Learn how to calculate a linear regression equation that predicts price per share based on annual dividends. This analysis uses real data from 30 companies. The regression equation is P = 28.9367 + 2.4050 * D, where P is the price per share and D is the dividend.

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