In order for applicants to work for the foreign-service department, they must take a test in the language of the country where they plan to work. The data below shows the relationship between the number of years that applicants have studied a particular language and the grades they received on the proficiency exam. Find the equation of the regression line for the given data Number of years, x 3 4 6 2 7 3 Grades on test, y 61 68 75 82 73 90 58 93 72 O A. y=6.910x-46.261 O B. ý= 46.261x+6.910 OC. y=6910x+ 46.261 O D. y= 46.261x-6.910

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### Understanding Regression Analysis for Language Proficiency Exams

In order for applicants to work for the foreign-service department, they must take a test in the language of the country where they plan to work. The data below shows the relationship between the number of years that applicants have studied a particular language and the grades they received on the proficiency exam. Your task is to find the equation of the regression line for the given data.

#### Data Table:
- **Number of years, x:**
  - 3, 4, 4, 5, 3, 6, 2, 7
- **Grades on test, y:**
  - 61, 68, 75, 82, 73, 90, 58, 93, 72
  
#### Options for Regression Line Equation:

- **Option A:** 
  - \(\hat{y} = 6.910x - 46.261\)
  
- **Option B:** 
  - \(\hat{y} = 46.261x + 6.910\)
  
- **Option C:** 
  - \(\hat{y} = 6.910x + 46.261\)
  
- **Option D:** 
  - \(\hat{y} = 46.261x - 6.910\)
  
#### Explanation:

To find the best fit line, or regression line, one typically uses the least squares method, which minimizes the sum of the squared differences between observed and predicted values. The regression equation is typically represented in the form:

\[
\hat{y} = a + bx
\]

Where:
- \(\hat{y}\) is the predicted value.
- \(a\) is the y-intercept.
- \(b\) is the slope of the line.

#### Conclusion:

After assessing the options provided, determine which equation best fits the data by calculating or using statistical software to find the most accurate equation reflecting the relationship between study years and test grades. This guides decisions and predictions related to language proficiency outcomes based on study duration.
Transcribed Image Text:### Understanding Regression Analysis for Language Proficiency Exams In order for applicants to work for the foreign-service department, they must take a test in the language of the country where they plan to work. The data below shows the relationship between the number of years that applicants have studied a particular language and the grades they received on the proficiency exam. Your task is to find the equation of the regression line for the given data. #### Data Table: - **Number of years, x:** - 3, 4, 4, 5, 3, 6, 2, 7 - **Grades on test, y:** - 61, 68, 75, 82, 73, 90, 58, 93, 72 #### Options for Regression Line Equation: - **Option A:** - \(\hat{y} = 6.910x - 46.261\) - **Option B:** - \(\hat{y} = 46.261x + 6.910\) - **Option C:** - \(\hat{y} = 6.910x + 46.261\) - **Option D:** - \(\hat{y} = 46.261x - 6.910\) #### Explanation: To find the best fit line, or regression line, one typically uses the least squares method, which minimizes the sum of the squared differences between observed and predicted values. The regression equation is typically represented in the form: \[ \hat{y} = a + bx \] Where: - \(\hat{y}\) is the predicted value. - \(a\) is the y-intercept. - \(b\) is the slope of the line. #### Conclusion: After assessing the options provided, determine which equation best fits the data by calculating or using statistical software to find the most accurate equation reflecting the relationship between study years and test grades. This guides decisions and predictions related to language proficiency outcomes based on study duration.
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