A survey is conducted on 700 Californians older than 30 years of age. The study wants to obtain inference on the relationship between years of education and yearly income in dollars. The response variable is income in dollars and the explanatory variable is years of education. A simple linear regression model is fit, and the output from R is below: Im(formula = Income ~ Education, data = CA) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 25200.25 1488.94 16.93 3.08e-10 *** Education 2905.35 112.61 25.80 1.49e-12 *** Residual standard error: 32400 on 698 degrees of freedom Multiple R-squared: 0.7602

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### Analysis of the Relationship Between Education and Income in California

**Abstract:**
A survey has been conducted on 700 Californians who are older than 30 years of age. The objective of this study is to investigate the relationship between years of education and yearly income in dollars. In this study, income in dollars is the response variable, and years of education is the explanatory variable.

**Methodology:**
To analyze the data, a simple linear regression model is employed. The regression model is fitted using statistical software R, and the output is as follows:

```R
lm(formula = Income ~ Education, data = CA)
```

**Summary of Results:**

**Coefficients:**
| **Term**        | **Estimate** | **Std. Error** | **t value** | **Pr(>|t|)**    |
|-----------------|--------------|----------------|-------------|-----------------|
| (Intercept)     | 25200.25     | 1488.94        | 16.93       | 3.08e-10 ***    |
| Education       | 2905.35      | 112.61         | 25.80       | 1.49e-12 ***    |

- **Intercept:**
  - **Estimate:** 25200.25
  - **Std. Error:** 1488.94
  - **t value:** 16.93
  - **Pr(>|t|):** 3.08e-10
  
- **Education:**
  - **Estimate:** 2905.35
  - **Std. Error:** 112.61
  - **t value:** 25.80
  - **Pr(>|t|):** 1.49e-12

**Residual Standard Error:**
32400, on 698 degrees of freedom

**Multiple R-squared:**
0.7602

**Interpretation:**
- The intercept (\( \beta_0 \)) is 25200.25. This suggests that, on average, the baseline income is $25,200 for someone with zero years of education. 
- The coefficient for years of education (\( \beta_1 \)) is 2905.35. This indicates that for each additional year of education, the yearly income increases by approximately $2,905.35.
- Both coefficients are statistically significant (p-values < \( 0
Transcribed Image Text:### Analysis of the Relationship Between Education and Income in California **Abstract:** A survey has been conducted on 700 Californians who are older than 30 years of age. The objective of this study is to investigate the relationship between years of education and yearly income in dollars. In this study, income in dollars is the response variable, and years of education is the explanatory variable. **Methodology:** To analyze the data, a simple linear regression model is employed. The regression model is fitted using statistical software R, and the output is as follows: ```R lm(formula = Income ~ Education, data = CA) ``` **Summary of Results:** **Coefficients:** | **Term** | **Estimate** | **Std. Error** | **t value** | **Pr(>|t|)** | |-----------------|--------------|----------------|-------------|-----------------| | (Intercept) | 25200.25 | 1488.94 | 16.93 | 3.08e-10 *** | | Education | 2905.35 | 112.61 | 25.80 | 1.49e-12 *** | - **Intercept:** - **Estimate:** 25200.25 - **Std. Error:** 1488.94 - **t value:** 16.93 - **Pr(>|t|):** 3.08e-10 - **Education:** - **Estimate:** 2905.35 - **Std. Error:** 112.61 - **t value:** 25.80 - **Pr(>|t|):** 1.49e-12 **Residual Standard Error:** 32400, on 698 degrees of freedom **Multiple R-squared:** 0.7602 **Interpretation:** - The intercept (\( \beta_0 \)) is 25200.25. This suggests that, on average, the baseline income is $25,200 for someone with zero years of education. - The coefficient for years of education (\( \beta_1 \)) is 2905.35. This indicates that for each additional year of education, the yearly income increases by approximately $2,905.35. - Both coefficients are statistically significant (p-values < \( 0
### Question: 

**What is the estimated expected income for someone with 20 years of education?**

[Text Box for User Input] 

---

#### Explanation:

This is an educational question meant to evaluate the relationship between educational attainment and expected income. Students are asked to estimate the expected income for an individual who has completed 20 years of education, typically equivalent to achieving a doctorate or professional degree. 

---

### Instructions:

Please enter the estimated expected income in the text box provided. Consider using data sources such as salary surveys, government publications, and academic studies to inform your answer.
Transcribed Image Text:### Question: **What is the estimated expected income for someone with 20 years of education?** [Text Box for User Input] --- #### Explanation: This is an educational question meant to evaluate the relationship between educational attainment and expected income. Students are asked to estimate the expected income for an individual who has completed 20 years of education, typically equivalent to achieving a doctorate or professional degree. --- ### Instructions: Please enter the estimated expected income in the text box provided. Consider using data sources such as salary surveys, government publications, and academic studies to inform your answer.
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