Is there a way to compute using Excel? ### Annual Revenue and Franchise Value DataThis table presents a comparison between the annual revenue and franchise value for various entities, with both financial figures expressed in millions of dollars.| Annual Revenue (millions of dollars) | Franchise Value (millions of dollars) ||--------------------------------------|---------------------------------------|| 244 | 742 || 201 | 542 || 262 | 849 || 197 | 511 || 277 | 823 || 218 | 473 || 179 | 346 || 224 | 637 || 229 | 601 || 202 | 474 || 196 | 452 || 187 | 375 || 166 | 371 || 226 | 593 || 235 | 730 |#### Analysis:- The highest annual revenue recorded in the dataset is 277 million dollars, corresponding to a franchise value of 823 million dollars.- The lowest annual revenue is 166 million dollars, paired with a franchise value of 371 million dollars.- The highest franchise value is 849 million dollars, associated with an annual revenue of 262 million dollars.- A general observation suggests a positive correlation between annual revenue and franchise value, although variations exist. The text discusses the relationship between the value of a sports franchise and its annual revenue, focusing on 15 major sports teams. The goal is to develop a linear regression model to predict the franchise value from annual revenue. It mentions a data table containing these values and instructs the user to complete parts (a) through (e) to understand this relationship.The task at hand is to construct a scatter plot and choose the correct graph from four options provided (A, B, C, D).**Description of Graphs:**- **Graph A**: Plots Annual Revenue ($M) on the y-axis against Franchise Value ($M) on the x-axis. The data points appear scattered without a clear linear trend.- **Graph B**: Plots Franchise Value ($M) on the y-axis against Annual Revenue ($M) on the x-axis. The data points appear to follow a positive linear trend.- **Graph C**: Similar to Graph A, with Annual Revenue ($M) on the y-axis and Franchise Value ($M) on the x-axis, displaying a scattered pattern of data points.- **Graph D**: Similar to Graph B, with Franchise Value ($M) on the y-axis and Annual Revenue ($M) on the x-axis, but with a more dispersed set of data points compared to Graph B.The task is to select the graph that correctly represents the relationship for constructing a linear regression model.

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Description: Is there a way to compute using Excel? ### Annual Revenue and Franchise Value DataThis table presents a comparison between the annual revenue and franchise value for various entities, with both financial figures expressed in millions of dollars.| Ann

a) Scatter plot: Steps to construct scatter plot in Excel: Enter the data for Annual Revenue and…

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The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The accompanying data table gives the valu revenue for 15 major sport teams. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue Complete parts (a) through (e) below. E Click the icon to view the table of franchise values and annual revenues. a. Construct a scatter plot. Choose the correct graph below. O A. OB. Oc. OD. E 3004 900- * 300- A 9004 al Revenue Chise Value (SM) al Revenue ($M) O chise Value ($M)

The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The accompanying data table gives the valu revenue for 15 major sport teams. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue Complete parts (a) through (e) below. E Click the icon to view the table of franchise values and annual revenues. a. Construct a scatter plot. Choose the correct graph below. O A. OB. Oc. OD. E 3004 900- * 300- A 9004 al Revenue Chise Value (SM) al Revenue ($M) O chise Value ($M)

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Is there a way to compute using Excel?

### Annual Revenue and Franchise Value Data

This table presents a comparison between the annual revenue and franchise value for various entities, with both financial figures expressed in millions of dollars.

| Annual Revenue (millions of dollars) | Franchise Value (millions of dollars) |
|--------------------------------------|---------------------------------------|
| 244 | 742 |
| 201 | 542 |
| 262 | 849 |
| 197 | 511 |
| 277 | 823 |
| 218 | 473 |
| 179 | 346 |
| 224 | 637 |
| 229 | 601 |
| 202 | 474 |
| 196 | 452 |
| 187 | 375 |
| 166 | 371 |
| 226 | 593 |
| 235 | 730 |

#### Analysis:

- The highest annual revenue recorded in the dataset is 277 million dollars, corresponding to a franchise value of 823 million dollars.
- The lowest annual revenue is 166 million dollars, paired with a franchise value of 371 million dollars.
- The highest franchise value is 849 million dollars, associated with an annual revenue of 262 million dollars.
- A general observation suggests a positive correlation between annual revenue and franchise value, although variations exist.

The text discusses the relationship between the value of a sports franchise and its annual revenue, focusing on 15 major sports teams. The goal is to develop a linear regression model to predict the franchise value from annual revenue. It mentions a data table containing these values and instructs the user to complete parts (a) through (e) to understand this relationship.

The task at hand is to construct a scatter plot and choose the correct graph from four options provided (A, B, C, D).

**Description of Graphs:**

- **Graph A**: Plots Annual Revenue ($M) on the y-axis against Franchise Value ($M) on the x-axis. The data points appear scattered without a clear linear trend.

- **Graph B**: Plots Franchise Value ($M) on the y-axis against Annual Revenue ($M) on the x-axis. The data points appear to follow a positive linear trend.

- **Graph C**: Similar to Graph A, with Annual Revenue ($M) on the y-axis and Franchise Value ($M) on the x-axis, displaying a scattered pattern of data points.

- **Graph D**: Similar to Graph B, with Franchise Value ($M) on the y-axis and Annual Revenue ($M) on the x-axis, but with a more dispersed set of data points compared to Graph B.

The task is to select the graph that correctly represents the relationship for constructing a linear regression model.

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