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Question2: Use the following formulas to fill the blank ý = b0 + b1x b1 =ry Sx >r = b1: Sy b0 = y- blx → ỹ = b0 + b1x %3D 9-b0 b1

Question2: Use the following formulas to fill the blank ý = b0 + b1x b1 =ry Sx >r = b1: Sy b0 = y- blx → ỹ = b0 + b1x %3D 9-b0 b1

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Use the following formulas to fill the Blank

**Question 2: Use the following formulas to fill the blanks** \[ \hat{y} = b0 + b1x \] \[ b1 = \frac{r \cdot S_y}{S_x} \] \[ b0 = \bar{y} - b1\bar{x} \] \[ r = \frac{b1 \cdot S_x}{S_y} \] \[ \bar{y} = b0 + b1\bar{x} \] \[ \bar{x} = \frac{\bar{y} - b0}{b1} \] | | \( \bar{x} \) | \( \bar{y} \) | \( S_x \) | \( S_y \) | \( r \) | \( r_{xy} \) | \( b_0 \) | \( b_1 \) | \( \hat{y} \) | \( \hat{y} = b_0 + b_1x \) | |----|-----------|-----------|--------|--------|-------|------|-----|-----|---------|---------------------| | 1) | 10 | 20 | 2 | 3 | 0.5 | 12.5 | 0.75| ? | ? | | | 2) | 2 | 7.2 | 0.06 | 1.2 | 0.4 | ? | ? | ? | ? | | | 3) | 12 | 152 | 6 | 30 | ? | ? | ? | ? | ? | | | 4) | 2.5 | ? | 1.2 | 100 | ? | ? | -100| 50 | ? | \(\hat{y} = 200 - 4x\) | ### Explanation of Formulas - **Linear Regression Equation**: \(\hat{y} = b0 + b1x\) helps predict the dependent variable (\(y\)) based on the independent variable (\(x\)). - **Slope \(b1\)**: Calculated as \(\frac{r \cdot S_y}{S_x}\), represents the rate at
Transcribed Image Text:**Question 2: Use the following formulas to fill the blanks** \[ \hat{y} = b0 + b1x \] \[ b1 = \frac{r \cdot S_y}{S_x} \] \[ b0 = \bar{y} - b1\bar{x} \] \[ r = \frac{b1 \cdot S_x}{S_y} \] \[ \bar{y} = b0 + b1\bar{x} \] \[ \bar{x} = \frac{\bar{y} - b0}{b1} \] | | \( \bar{x} \) | \( \bar{y} \) | \( S_x \) | \( S_y \) | \( r \) | \( r_{xy} \) | \( b_0 \) | \( b_1 \) | \( \hat{y} \) | \( \hat{y} = b_0 + b_1x \) | |----|-----------|-----------|--------|--------|-------|------|-----|-----|---------|---------------------| | 1) | 10 | 20 | 2 | 3 | 0.5 | 12.5 | 0.75| ? | ? | | | 2) | 2 | 7.2 | 0.06 | 1.2 | 0.4 | ? | ? | ? | ? | | | 3) | 12 | 152 | 6 | 30 | ? | ? | ? | ? | ? | | | 4) | 2.5 | ? | 1.2 | 100 | ? | ? | -100| 50 | ? | \(\hat{y} = 200 - 4x\) | ### Explanation of Formulas - **Linear Regression Equation**: \(\hat{y} = b0 + b1x\) helps predict the dependent variable (\(y\)) based on the independent variable (\(x\)). - **Slope \(b1\)**: Calculated as \(\frac{r \cdot S_y}{S_x}\), represents the rate at
Expert Solution
Step 1

1)

The value of b0 is 12.5, and b1 is 0.75.

The regression equation is,

y^=b0+b1x=12.5+0.75x

Thus, the regression equation is y^=12.5+0.75x.

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