SSION EQUATIONS. FIll In the missing information in the following table 23a+ bx r 10 20 0.5 0.06 7.2 1.2 -0.4 9= 200-4x 9 = -100+50x 12 -0.8 2.5 1.2 100

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**Regression Equations: Fill in the Missing Information in the Following Table**

| \(\bar{x}\)  | \(s_x\) | \(\bar{y}\)  | \(s_y\) | \(r\)  | \(\hat{y} = a + bx\)          |
|-------------|--------|-------------|--------|-------|-----------------------------|
| 10          | 2      | 20          | 3      | 0.5   |                             |
| 2           | 0.06   | 7.2         | 1.2    | -0.4  |                             |
| 12          | 6      |             |        | -0.8  | \(\hat{y} = 200 - 4x\)      |
| 2.5         | 1.2    | 100         |        |       | \(\hat{y} = -100 + 50x\)    |

**Table Explanation:**
This table presents data for calculating linear regression equations. The columns represent statistical parameters:

- \(\bar{x}\): Mean of the x-values.
- \(s_x\): Standard deviation of the x-values.
- \(\bar{y}\): Mean of the y-values.
- \(s_y\): Standard deviation of the y-values.
- \(r\): Correlation coefficient between x and y.
- \(\hat{y} = a + bx\): Regression equation of the line where \(a\) is the y-intercept and \(b\) is the slope.

Each row represents a separate regression scenario, with some information missing and asks the reader to fill it in using their knowledge of statistics and the relationships between the variables.
Transcribed Image Text:**Regression Equations: Fill in the Missing Information in the Following Table** | \(\bar{x}\) | \(s_x\) | \(\bar{y}\) | \(s_y\) | \(r\) | \(\hat{y} = a + bx\) | |-------------|--------|-------------|--------|-------|-----------------------------| | 10 | 2 | 20 | 3 | 0.5 | | | 2 | 0.06 | 7.2 | 1.2 | -0.4 | | | 12 | 6 | | | -0.8 | \(\hat{y} = 200 - 4x\) | | 2.5 | 1.2 | 100 | | | \(\hat{y} = -100 + 50x\) | **Table Explanation:** This table presents data for calculating linear regression equations. The columns represent statistical parameters: - \(\bar{x}\): Mean of the x-values. - \(s_x\): Standard deviation of the x-values. - \(\bar{y}\): Mean of the y-values. - \(s_y\): Standard deviation of the y-values. - \(r\): Correlation coefficient between x and y. - \(\hat{y} = a + bx\): Regression equation of the line where \(a\) is the y-intercept and \(b\) is the slope. Each row represents a separate regression scenario, with some information missing and asks the reader to fill it in using their knowledge of statistics and the relationships between the variables.
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