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Linear Interpolation/Extrapolation The following plot presents the relationship between the salaries earned by 9 employees and their years of experience. 1. Predict the salary an employee might earn after working for 6 years.  $ ____  (Report your answer in 1000s of dollars and include two decimal places.) 2. If an employee makes $47,000 how many years do you expect they have been working at the company?  ____ (Round to the nearest year.)

Linear Interpolation/Extrapolation The following plot presents the relationship between the salaries earned by 9 employees and their years of experience. 1. Predict the salary an employee might earn after working for 6 years.  $ ____  (Report your answer in 1000s of dollars and include two decimal places.) 2. If an employee makes $47,000 how many years do you expect they have been working at the company?  ____ (Round to the nearest year.)

MATLAB: An Introduction with Applications
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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Linear Interpolation/Extrapolation

The following plot presents the relationship between the salaries earned by 9 employees and their years of experience.

1. Predict the salary an employee might earn after working for 6 years.
 $ ____  (Report your answer in 1000s of dollars and include two decimal places.)

2. If an employee makes $47,000 how many years do you expect they have been working at the company?
 ____ (Round to the nearest year.)

**Job Experience vs. Salary** This graph displays the relationship between years of job experience and salary in thousands of dollars. The x-axis represents the "Years of Experience," ranging from 0 to 18 years. The y-axis denotes "Salary in $1000 of Dollars," starting at $0 and reaching $100,000. Key Details: - **Data Points**: Several blue dots indicate individual data points representing different combinations of years of experience and corresponding salaries. - **Trend Line**: A dotted line represents the linear trend line fitted to the data points. - **Equation**: The trend line is expressed by the equation \( y = 4.7996x + 9.1809 \), where \( y \) stands for salary, and \( x \) for years of experience. - **R² Value**: The \( R^2 \) value is 0.9531, indicating a strong correlation between job experience and salary, suggesting that the model explains approximately 95.31% of the variability in salary based on experience.
Transcribed Image Text:**Job Experience vs. Salary** This graph displays the relationship between years of job experience and salary in thousands of dollars. The x-axis represents the "Years of Experience," ranging from 0 to 18 years. The y-axis denotes "Salary in $1000 of Dollars," starting at $0 and reaching $100,000. Key Details: - **Data Points**: Several blue dots indicate individual data points representing different combinations of years of experience and corresponding salaries. - **Trend Line**: A dotted line represents the linear trend line fitted to the data points. - **Equation**: The trend line is expressed by the equation \( y = 4.7996x + 9.1809 \), where \( y \) stands for salary, and \( x \) for years of experience. - **R² Value**: The \( R^2 \) value is 0.9531, indicating a strong correlation between job experience and salary, suggesting that the model explains approximately 95.31% of the variability in salary based on experience.
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