A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN: 9780134753119
Author: Sheldon Ross
Publisher: PEARSON
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**Regression Analysis of Used Car Prices**

In order to examine the relationship between the selling price of a used car and its age, an analyst uses data from 20 recent transactions and estimates the equation: 

\[ \text{Price} = \beta_0 + \beta_1 \text{Age} + \varepsilon \]

A portion of the regression results is shown in the accompanying table.

|                | Coefficients | Standard Error | t Stat | p-value   |
|----------------|--------------|----------------|--------|-----------|
| Intercept      | 21,268.91    | 732.41         | 29.040 | 1.42E-16  |
| Age            | -1,201.23    | 128.98         | -       | 2.64E-08  |

1. **Hypotheses Specification:**

   Specify the competing hypotheses to determine whether the selling price of a used car and its age are linearly related.

   - \( H_0: \beta_1 \ge 0; \) \( H_A: \beta_1 < 0 \)
   - \( H_0: \beta_1 = 0; \) \( H_A: \beta_1 \neq 0 \)
   - \( H_0: \beta_1 \le 0; \) \( H_A: \beta_1 > 0 \)

2. **Calculate the Test Statistic:**

   Calculate the value of the test statistic. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.)

   - Test statistic box for input.

3. **Find the p-value:**

   - \( \text{p-value} \ge 0.10 \)
   - \( 0.05 \le \text{p-value} < 0.10 \)
   - \( 0.02 \le \text{p-value} < 0.05 \)
   - \( 0.01 \le \text{p-value} < 0.02 \)
   - \( \text{p-value} < 0.01 \)

4. **Significance at the 5% Level:**

   At the 5% significance level, is the age of a used car significant in explaining its selling price?

   - Conclusion box for input: " , we conclude that the
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Transcribed Image Text:**Regression Analysis of Used Car Prices** In order to examine the relationship between the selling price of a used car and its age, an analyst uses data from 20 recent transactions and estimates the equation: \[ \text{Price} = \beta_0 + \beta_1 \text{Age} + \varepsilon \] A portion of the regression results is shown in the accompanying table. | | Coefficients | Standard Error | t Stat | p-value | |----------------|--------------|----------------|--------|-----------| | Intercept | 21,268.91 | 732.41 | 29.040 | 1.42E-16 | | Age | -1,201.23 | 128.98 | - | 2.64E-08 | 1. **Hypotheses Specification:** Specify the competing hypotheses to determine whether the selling price of a used car and its age are linearly related. - \( H_0: \beta_1 \ge 0; \) \( H_A: \beta_1 < 0 \) - \( H_0: \beta_1 = 0; \) \( H_A: \beta_1 \neq 0 \) - \( H_0: \beta_1 \le 0; \) \( H_A: \beta_1 > 0 \) 2. **Calculate the Test Statistic:** Calculate the value of the test statistic. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.) - Test statistic box for input. 3. **Find the p-value:** - \( \text{p-value} \ge 0.10 \) - \( 0.05 \le \text{p-value} < 0.10 \) - \( 0.02 \le \text{p-value} < 0.05 \) - \( 0.01 \le \text{p-value} < 0.02 \) - \( \text{p-value} < 0.01 \) 4. **Significance at the 5% Level:** At the 5% significance level, is the age of a used car significant in explaining its selling price? - Conclusion box for input: " , we conclude that the
**d-1.** Conduct a hypothesis test at the 5% significance level in order to determine if \( a_1 \) differs from -1,000. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.)

**Test statistic:** [Text box]

**d-2.** Find the \( p \)-value.

- \( 0.05 \leq \) \( p \)-value \( < 0.10 \)
- \( 0.02 \leq \) \( p \)-value \( < 0.05 \)
- \( 0.01 \leq \) \( p \)-value \( < 0.02 \)
- \( p \)-value \( < 0.01 \)
- \( p \)-value \( \geq 0.10 \)

**d-3.** What is the conclusion to the test?

\[ H_0, \text{ we} \] [Dropdown] conclude that \(\beta_1 \neq -1,000 \)
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Transcribed Image Text:**d-1.** Conduct a hypothesis test at the 5% significance level in order to determine if \( a_1 \) differs from -1,000. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.) **Test statistic:** [Text box] **d-2.** Find the \( p \)-value. - \( 0.05 \leq \) \( p \)-value \( < 0.10 \) - \( 0.02 \leq \) \( p \)-value \( < 0.05 \) - \( 0.01 \leq \) \( p \)-value \( < 0.02 \) - \( p \)-value \( < 0.01 \) - \( p \)-value \( \geq 0.10 \) **d-3.** What is the conclusion to the test? \[ H_0, \text{ we} \] [Dropdown] conclude that \(\beta_1 \neq -1,000 \)
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