A regression model to predict Y, the state burglary rate per 100.000 people, used the following four state predictors: X₁ = median age, X₂ = number of bankruptcies per 1,000 population, X₂ = federal expenditures per capita (a leading predictor), and X₁ = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 50 people, calculate the calc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.) Predictor Intercept AgeMed Bankrupt FedSpend HSGrad% Answer is complete but not entirely correct. tcalc 5.2526 -2.1764✔ Coefficient 4,198.5808 -27.3540 17.4893 -0.0124 -29.0314 SE 799.3395 12.5687 12.4033 0.0176 7.1268 p-value 0.0000 0.0348 1.4101 0.2935 -0.7045 0.4848 -4.0736✔ 0.0002
A regression model to predict Y, the state burglary rate per 100.000 people, used the following four state predictors: X₁ = median age, X₂ = number of bankruptcies per 1,000 population, X₂ = federal expenditures per capita (a leading predictor), and X₁ = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 50 people, calculate the calc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.) Predictor Intercept AgeMed Bankrupt FedSpend HSGrad% Answer is complete but not entirely correct. tcalc 5.2526 -2.1764✔ Coefficient 4,198.5808 -27.3540 17.4893 -0.0124 -29.0314 SE 799.3395 12.5687 12.4033 0.0176 7.1268 p-value 0.0000 0.0348 1.4101 0.2935 -0.7045 0.4848 -4.0736✔ 0.0002
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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![A regression model to predict \( Y \), the state burglary rate per 100,000 people, used the following four state predictors:
- \( X_1 \) = median age
- \( X_2 \) = number of bankruptcies per 1,000 population
- \( X_3 \) = federal expenditures per capita (a leading predictor)
- \( X_4 \) = high school graduation percentage.
\[ \text{(Click here for the Excel Data File)} \]
**(a)** Using a sample size of 50 people, calculate the \( t_{\text{calc}} \) and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.)
| Predictor | Coefficient | SE | \( t_{\text{calc}} \) | p-value |
|-----------|-------------|--------|----------------|---------|
| Intercept | 4,188.5808 | 799.3395 | 5.2526 | 0.0000 |
| AgeMed | -27.3540 | 12.5887 | -2.1764 | 0.0348 |
| Bankrupt | 17.4893 | 12.4033 | 1.4101 | 0.2385 |
| FedSpend | -0.0124 | 0.0176 | -0.7045 | 0.4848 |
| HSGrad% | -29.0314 | 7.1268 | -4.0736 | 0.0002 |
**Note:** The answer is complete but not entirely correct.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fff6f9a4d-2084-42ea-abf6-3325fa2ca826%2F023d810a-3157-41d6-add8-b39a194a602f%2Fc1zr09u_processed.png&w=3840&q=75)
Transcribed Image Text:A regression model to predict \( Y \), the state burglary rate per 100,000 people, used the following four state predictors:
- \( X_1 \) = median age
- \( X_2 \) = number of bankruptcies per 1,000 population
- \( X_3 \) = federal expenditures per capita (a leading predictor)
- \( X_4 \) = high school graduation percentage.
\[ \text{(Click here for the Excel Data File)} \]
**(a)** Using a sample size of 50 people, calculate the \( t_{\text{calc}} \) and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.)
| Predictor | Coefficient | SE | \( t_{\text{calc}} \) | p-value |
|-----------|-------------|--------|----------------|---------|
| Intercept | 4,188.5808 | 799.3395 | 5.2526 | 0.0000 |
| AgeMed | -27.3540 | 12.5887 | -2.1764 | 0.0348 |
| Bankrupt | 17.4893 | 12.4033 | 1.4101 | 0.2385 |
| FedSpend | -0.0124 | 0.0176 | -0.7045 | 0.4848 |
| HSGrad% | -29.0314 | 7.1268 | -4.0736 | 0.0002 |
**Note:** The answer is complete but not entirely correct.
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