Different hotels in a certain area are randomly selected, and their ratings and prices were obtained online. Using technology, with x representing the ratings and y representing price, we find that the regression equation has a slope of 130 and a y-intercept of -350. Complete parts (a) and (b) below. a. What is the equation of the regression line? Select the correct choice below and fill in the answer boxes to complete your choice. OA OB. yx Oc.;-* OD. y=x b. What does the symbol y represent? OA. The symbol y represents the expected price when the hotel's rating is 0. OB. The symbol y represents the average price of hotels in the area. OC. The symbol y represents the predicted value of price. OD. The symbol y represents the amount that price increases with a 1-point increase in rating.

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### Regression Analysis in Hotel Pricing

Different hotels in a certain area are randomly selected, and their ratings and prices were obtained online. Using technology, with \( x \) representing the ratings and \( y \) representing price, we find that the regression equation has a slope of 130 and a y-intercept of -350. Complete parts (a) and (b) below.

#### a. What is the equation of the regression line?

Select the correct choice below and fill in the answer boxes to complete your choice.

- **A.** \(\hat{y} = [ \quad ] + ( [ \quad ] ) x \)
- **B.** \(\hat{y} = [ \quad ] - ( [ \quad ] ) x \)
- **C.** \(\hat{y} = [ \quad ] + ( [ \quad ] ) x \)
- **D.** \(\hat{y} = [ \quad ] - ( [ \quad ] ) x \)

#### b. What does the symbol \(\hat{y}\) represent?

- **A.** The symbol \(\hat{y}\) represents the expected price when the hotel's rating is 0.
- **B.** The symbol \(\hat{y}\) represents the average price of hotels in the area.
- **C.** The symbol \(\hat{y}\) represents the predicted value of price.
- **D.** The symbol \(\hat{y}\) represents the amount that price increases with a 1-point increase in rating.

### Explanation and Solution:

#### Regression Line Equation

For a regression equation of the form \(\hat{y} = mx + b\), where \(m\) represents the slope and \(b\) represents the y-intercept:
- Given the slope (\(m\)) is 130 and the y-intercept (\(b\)) is -350.
- The correct equation is: \[\hat{y} = -350 + 130x\]

Thus, the correct answer for part (a) is:
\[ \mathbf{A.} \ \hat{y} = -350 + (130) x \]

#### Interpretation of \(\hat{y}\)

The symbol \(\hat{y}\) in regression analysis typically represents the predicted value of the dependent variable based on the regression equation and the corresponding value of the independent variable.
Transcribed Image Text:### Regression Analysis in Hotel Pricing Different hotels in a certain area are randomly selected, and their ratings and prices were obtained online. Using technology, with \( x \) representing the ratings and \( y \) representing price, we find that the regression equation has a slope of 130 and a y-intercept of -350. Complete parts (a) and (b) below. #### a. What is the equation of the regression line? Select the correct choice below and fill in the answer boxes to complete your choice. - **A.** \(\hat{y} = [ \quad ] + ( [ \quad ] ) x \) - **B.** \(\hat{y} = [ \quad ] - ( [ \quad ] ) x \) - **C.** \(\hat{y} = [ \quad ] + ( [ \quad ] ) x \) - **D.** \(\hat{y} = [ \quad ] - ( [ \quad ] ) x \) #### b. What does the symbol \(\hat{y}\) represent? - **A.** The symbol \(\hat{y}\) represents the expected price when the hotel's rating is 0. - **B.** The symbol \(\hat{y}\) represents the average price of hotels in the area. - **C.** The symbol \(\hat{y}\) represents the predicted value of price. - **D.** The symbol \(\hat{y}\) represents the amount that price increases with a 1-point increase in rating. ### Explanation and Solution: #### Regression Line Equation For a regression equation of the form \(\hat{y} = mx + b\), where \(m\) represents the slope and \(b\) represents the y-intercept: - Given the slope (\(m\)) is 130 and the y-intercept (\(b\)) is -350. - The correct equation is: \[\hat{y} = -350 + 130x\] Thus, the correct answer for part (a) is: \[ \mathbf{A.} \ \hat{y} = -350 + (130) x \] #### Interpretation of \(\hat{y}\) The symbol \(\hat{y}\) in regression analysis typically represents the predicted value of the dependent variable based on the regression equation and the corresponding value of the independent variable.
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