Consider the following data for a dependent variable y and two independent variables, x₁ and x₂. X1 X2 30 47 25 51 51 74 36 59 12 94 10 108. 17 40 5 94 y 16 178 112 19 175 7 170 12 117 13 142 76 16 211 me estimated regression equation for these data is y = -18.36827 +2.01019x₁ +4.73781x2. ere, SST = 15,182.9, SSR = 14,052.2, Sb₁ = 0.24712, and Sp₂ = 0.94844. (SST represents the Total Sum of Squares presents the Regression Sum of Squares) a) Test for a significant relationship among X₁, X₂, and y. Use α = 0.05. State the null and alternative hypotheses. O Ho: B1 = B2 = 0 o Ho Bì > B2 H₂: B₁ ≤ B₂ H₂: : One or more of the parameters is not equal to zero. o Ho Bi
Consider the following data for a dependent variable y and two independent variables, x₁ and x₂. X1 X2 30 47 25 51 51 74 36 59 12 94 10 108. 17 40 5 94 y 16 178 112 19 175 7 170 12 117 13 142 76 16 211 me estimated regression equation for these data is y = -18.36827 +2.01019x₁ +4.73781x2. ere, SST = 15,182.9, SSR = 14,052.2, Sb₁ = 0.24712, and Sp₂ = 0.94844. (SST represents the Total Sum of Squares presents the Regression Sum of Squares) a) Test for a significant relationship among X₁, X₂, and y. Use α = 0.05. State the null and alternative hypotheses. O Ho: B1 = B2 = 0 o Ho Bì > B2 H₂: B₁ ≤ B₂ H₂: : One or more of the parameters is not equal to zero. o Ho Bi
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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Problem 1P
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Need help solving a b and c
![### Regression Analysis of Dependent and Independent Variables
#### Data Table
The following data is provided for a dependent variable \( y \) and two independent variables, \( x_1 \) and \( x_2 \):
| \( x_1 \) | \( x_2 \) | \( y \) |
|-----------|-----------|---------|
| 30 | 12 | 94 |
| 47 | 10 | 108 |
| 25 | 17 | 112 |
| 51 | 16 | 178 |
| 40 | 5 | 94 |
| 51 | 19 | 175 |
| 74 | 17 | 170 |
| 36 | 12 | 117 |
| 59 | 13 | 142 |
| 76 | 16 | 211 |
#### Estimated Regression Equation
The estimated regression equation based on the given data is:
\[
\hat{y} = -18.36827 + 2.01019x_1 + 4.73781x_2
\]
#### Sum of Squares
- Total Sum of Squares (SST): 15,182.9
- Regression Sum of Squares (SSR): 14,052.2
- Standard error of \( x_1 \) (\( s_{b_1} \)): 0.24712
- Standard error of \( x_2 \) (\( s_{b_2} \)): 0.94844
#### Hypothesis Testing
**Objective:** Test for a significant relationship among \( x_1 \), \( x_2 \), and \( y \). Use \( \alpha = 0.05 \).
**Hypothesis:**
- **\( H_0 \):** \(\beta_1 = \beta_2 = 0\)
- **\( H_a \):** One or more of the parameters is not equal to zero.
Choices:
- \( H_0 \): \(\beta_1 > \beta_2 \)
\( H_a \): \(\beta_1 \leq \beta_2 \)
- \( H_0 \): \(\beta_1 \neq 0 \) and \(\beta_2 \neq](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F93e02f2d-b0b4-40f2-b59c-ee2919cc5490%2F38fc1fe0-42f2-48ae-a92b-b08e7af5f7f5%2Fvdtemy_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### Regression Analysis of Dependent and Independent Variables
#### Data Table
The following data is provided for a dependent variable \( y \) and two independent variables, \( x_1 \) and \( x_2 \):
| \( x_1 \) | \( x_2 \) | \( y \) |
|-----------|-----------|---------|
| 30 | 12 | 94 |
| 47 | 10 | 108 |
| 25 | 17 | 112 |
| 51 | 16 | 178 |
| 40 | 5 | 94 |
| 51 | 19 | 175 |
| 74 | 17 | 170 |
| 36 | 12 | 117 |
| 59 | 13 | 142 |
| 76 | 16 | 211 |
#### Estimated Regression Equation
The estimated regression equation based on the given data is:
\[
\hat{y} = -18.36827 + 2.01019x_1 + 4.73781x_2
\]
#### Sum of Squares
- Total Sum of Squares (SST): 15,182.9
- Regression Sum of Squares (SSR): 14,052.2
- Standard error of \( x_1 \) (\( s_{b_1} \)): 0.24712
- Standard error of \( x_2 \) (\( s_{b_2} \)): 0.94844
#### Hypothesis Testing
**Objective:** Test for a significant relationship among \( x_1 \), \( x_2 \), and \( y \). Use \( \alpha = 0.05 \).
**Hypothesis:**
- **\( H_0 \):** \(\beta_1 = \beta_2 = 0\)
- **\( H_a \):** One or more of the parameters is not equal to zero.
Choices:
- \( H_0 \): \(\beta_1 > \beta_2 \)
\( H_a \): \(\beta_1 \leq \beta_2 \)
- \( H_0 \): \(\beta_1 \neq 0 \) and \(\beta_2 \neq
![### Statistical Significance Testing
**(b) Is \( \beta_1 \) significant? Use \(\alpha = 0.05\).**
#### Steps to Determine Significance:
1. **State the Null and Alternative Hypotheses.**
- Choose one of the following options:
- \( H_0: \beta_1 = 0 \)
\( H_a: \beta_1 \neq 0 \)
- \( H_0: \beta_1 \neq 0 \)
\( H_a: \beta_1 = 0 \)
- \( H_0: \beta_1 < 0 \)
\( H_a: \beta_1 \geq 0 \)
- \( H_0: \beta_1 > 0 \)
\( H_a: \beta_1 \leq 0 \)
- \( H_0: \beta_1 = 0 \)
\( H_a: \beta_1 > 0 \)
2. **Find the Value of the Test Statistic.**
- Round your answer to two decimal places.
\[ \text{Test Statistic} = \boxed{} \]
3. **Find the p-value.**
- Round your answer to three decimal places.
\[ p\text{-value} = \boxed{} \]
4. **State Your Conclusion.**
- Choose one of the following options:
- Do not reject \( H_0 \). There is insufficient evidence to conclude that \( \beta_1 \) is significant.
- Do not reject \( H_0 \). There is sufficient evidence to conclude that \( \beta_1 \) is significant.
- Reject \( H_0 \). There is insufficient evidence to conclude that \( \beta_1 \) is significant.
- Reject \( H_0 \). There is sufficient evidence to conclude that \( \beta_1 \) is significant.
---
**(c) Is \( \beta_2 \) significant? Use \(\alpha = 0.05\).**
#### Steps to Determine Significance:
1. **State the Null and Alternative Hypotheses.**
- Choose one of the following options:
- \( H_0: \beta_2 = 0 \)
\( H_a: \beta_2 > 0](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F93e02f2d-b0b4-40f2-b59c-ee2919cc5490%2F38fc1fe0-42f2-48ae-a92b-b08e7af5f7f5%2Fx6a10bh_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### Statistical Significance Testing
**(b) Is \( \beta_1 \) significant? Use \(\alpha = 0.05\).**
#### Steps to Determine Significance:
1. **State the Null and Alternative Hypotheses.**
- Choose one of the following options:
- \( H_0: \beta_1 = 0 \)
\( H_a: \beta_1 \neq 0 \)
- \( H_0: \beta_1 \neq 0 \)
\( H_a: \beta_1 = 0 \)
- \( H_0: \beta_1 < 0 \)
\( H_a: \beta_1 \geq 0 \)
- \( H_0: \beta_1 > 0 \)
\( H_a: \beta_1 \leq 0 \)
- \( H_0: \beta_1 = 0 \)
\( H_a: \beta_1 > 0 \)
2. **Find the Value of the Test Statistic.**
- Round your answer to two decimal places.
\[ \text{Test Statistic} = \boxed{} \]
3. **Find the p-value.**
- Round your answer to three decimal places.
\[ p\text{-value} = \boxed{} \]
4. **State Your Conclusion.**
- Choose one of the following options:
- Do not reject \( H_0 \). There is insufficient evidence to conclude that \( \beta_1 \) is significant.
- Do not reject \( H_0 \). There is sufficient evidence to conclude that \( \beta_1 \) is significant.
- Reject \( H_0 \). There is insufficient evidence to conclude that \( \beta_1 \) is significant.
- Reject \( H_0 \). There is sufficient evidence to conclude that \( \beta_1 \) is significant.
---
**(c) Is \( \beta_2 \) significant? Use \(\alpha = 0.05\).**
#### Steps to Determine Significance:
1. **State the Null and Alternative Hypotheses.**
- Choose one of the following options:
- \( H_0: \beta_2 = 0 \)
\( H_a: \beta_2 > 0
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