A random sample of 10 professional athletes produced the following data, where a is the number of endorsements the player has and y is the amount of money the player made (in millions of dollars). (Comma separated lists of the data are also provided below the table to ease in copying the data to R.) Number of Endorsements (x) Amount Player Made in Millions of Dollars (y) 5 7.6 2 6.6 6 15.3 7 3 4 4 7 3 4 z: 5, 2, 6, 7, 3, 4, 4, 7, 3, 4 y: 7.6, 6.6, 15.3, 9, 6, 14.4, 5.3, 12, 16.5, 3.4 1. Find the best fit line for the data. I 3. Predict the amount of money an athlete with 3 endorsements would make. million dollars 2. Graph the scatter plot of the data together with the best fit line using R. (This portion of the problem is not graded.) Question Help: Post to forum 9 6 14.4 5.3 12 16.5 3.4
A random sample of 10 professional athletes produced the following data, where a is the number of endorsements the player has and y is the amount of money the player made (in millions of dollars). (Comma separated lists of the data are also provided below the table to ease in copying the data to R.) Number of Endorsements (x) Amount Player Made in Millions of Dollars (y) 5 7.6 2 6.6 6 15.3 7 3 4 4 7 3 4 z: 5, 2, 6, 7, 3, 4, 4, 7, 3, 4 y: 7.6, 6.6, 15.3, 9, 6, 14.4, 5.3, 12, 16.5, 3.4 1. Find the best fit line for the data. I 3. Predict the amount of money an athlete with 3 endorsements would make. million dollars 2. Graph the scatter plot of the data together with the best fit line using R. (This portion of the problem is not graded.) Question Help: Post to forum 9 6 14.4 5.3 12 16.5 3.4
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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![A random sample of 10 professional athletes produced the following data, where \( x \) is the number of endorsements the player has and \( y \) is the amount of money the player made (in millions of dollars). (Comma separated lists of the data are also provided below to ease in copying the data to R.)
| Number of Endorsements (x) | Amount Player Made in Millions of Dollars (y) |
|----------------------------|---------------------------------------------|
| 5 | 7.6 |
| 2 | 6.6 |
| 6 | 15.3 |
| 7 | 9 |
| 3 | 6 |
| 4 | 14.4 |
| 4 | 5.3 |
| 7 | 12 |
| 3 | 16.5 |
| 4 | 3.4 |
\( x: 5, 2, 6, 7, 3, 4, 4, 7, 3, 4 \)
\( y: 7.6, 6.6, 15.3, 9, 6, 14.4, 5.3, 12, 16.5, 3.4 \)
1. Find the best fit line for the data.
\[ y = \_\_\_ + \_\_\_ x \]
2. Graph the scatter plot of the data together with the best fit line using R. (This portion of the problem is not graded.)
3. Predict the amount of money an athlete with 3 endorsements would make.
\[ \_\_\_ \text{ million dollars} \]
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Transcribed Image Text:A random sample of 10 professional athletes produced the following data, where \( x \) is the number of endorsements the player has and \( y \) is the amount of money the player made (in millions of dollars). (Comma separated lists of the data are also provided below to ease in copying the data to R.)
| Number of Endorsements (x) | Amount Player Made in Millions of Dollars (y) |
|----------------------------|---------------------------------------------|
| 5 | 7.6 |
| 2 | 6.6 |
| 6 | 15.3 |
| 7 | 9 |
| 3 | 6 |
| 4 | 14.4 |
| 4 | 5.3 |
| 7 | 12 |
| 3 | 16.5 |
| 4 | 3.4 |
\( x: 5, 2, 6, 7, 3, 4, 4, 7, 3, 4 \)
\( y: 7.6, 6.6, 15.3, 9, 6, 14.4, 5.3, 12, 16.5, 3.4 \)
1. Find the best fit line for the data.
\[ y = \_\_\_ + \_\_\_ x \]
2. Graph the scatter plot of the data together with the best fit line using R. (This portion of the problem is not graded.)
3. Predict the amount of money an athlete with 3 endorsements would make.
\[ \_\_\_ \text{ million dollars} \]
Question Help: Post to forum
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