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Certainly! Below is a transcription suitable for an educational website. --- **Credit Score Analysis:** An economist wants to determine the relationship between one's FICO score, \( x \), and the interest rate of a 36-month auto loan, \( y \). The given data represent the interest rate (in percent) a bank would offer on a 36-month auto loan for various FICO scores. | Credit Score, \( x \) | Interest Rate (percent), \( y \) | |-----------------------|----------------------------------| | 545 | 18.982 | | 595 | 17.967 | | 640 | 12.218 | | 675 | 8.612 | | 705 | 6.680 | | 750 | 5.150 | ### Tasks: a. **Find the least-squares regression line (Equation):** - Treat the FICO score, \( x \), as the explanatory variable and the interest rate, \( y \), as the response variable. b. **Determine the linear correlation coefficient** between compensation and stock return. - **Answer:** _______ c. **What type of linear relation exists between the two variables?** - **Answer:** _______ d. **Compute the coefficient of determination.** - **Answer:** _______ e. **Interpret the coefficient of determination.** - **Answer:** _______ f. **Draw a Scatter diagram of the data.** --- *For graph explanation:* - The **scatter diagram** would plot the FICO scores on the x-axis and the corresponding interest rates on the y-axis. Each point on the graph represents a pair of score and rate values. This visual representation can help identify patterns or the nature of the relationship between the two variables.

Certainly! Below is a transcription suitable for an educational website. --- **Credit Score Analysis:** An economist wants to determine the relationship between one's FICO score, \( x \), and the interest rate of a 36-month auto loan, \( y \). The given data represent the interest rate (in percent) a bank would offer on a 36-month auto loan for various FICO scores. | Credit Score, \( x \) | Interest Rate (percent), \( y \) | |-----------------------|----------------------------------| | 545 | 18.982 | | 595 | 17.967 | | 640 | 12.218 | | 675 | 8.612 | | 705 | 6.680 | | 750 | 5.150 | ### Tasks: a. **Find the least-squares regression line (Equation):** - Treat the FICO score, \( x \), as the explanatory variable and the interest rate, \( y \), as the response variable. b. **Determine the linear correlation coefficient** between compensation and stock return. - **Answer:** _______ c. **What type of linear relation exists between the two variables?** - **Answer:** _______ d. **Compute the coefficient of determination.** - **Answer:** _______ e. **Interpret the coefficient of determination.** - **Answer:** _______ f. **Draw a Scatter diagram of the data.** --- *For graph explanation:* - The **scatter diagram** would plot the FICO scores on the x-axis and the corresponding interest rates on the y-axis. Each point on the graph represents a pair of score and rate values. This visual representation can help identify patterns or the nature of the relationship between the two variables.

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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Certainly! Below is a transcription suitable for an educational website. --- **Credit Score Analysis:** An economist wants to determine the relationship between one's FICO score, \( x \), and the interest rate of a 36-month auto loan, \( y \). The given data represent the interest rate (in percent) a bank would offer on a 36-month auto loan for various FICO scores. | Credit Score, \( x \) | Interest Rate (percent), \( y \) | |-----------------------|----------------------------------| | 545 | 18.982 | | 595 | 17.967 | | 640 | 12.218 | | 675 | 8.612 | | 705 | 6.680 | | 750 | 5.150 | ### Tasks: a. **Find the least-squares regression line (Equation):** - Treat the FICO score, \( x \), as the explanatory variable and the interest rate, \( y \), as the response variable. b. **Determine the linear correlation coefficient** between compensation and stock return. - **Answer:** _______ c. **What type of linear relation exists between the two variables?** - **Answer:** _______ d. **Compute the coefficient of determination.** - **Answer:** _______ e. **Interpret the coefficient of determination.** - **Answer:** _______ f. **Draw a Scatter diagram of the data.** --- *For graph explanation:* - The **scatter diagram** would plot the FICO scores on the x-axis and the corresponding interest rates on the y-axis. Each point on the graph represents a pair of score and rate values. This visual representation can help identify patterns or the nature of the relationship between the two variables.
Transcribed Image Text:Certainly! Below is a transcription suitable for an educational website. --- **Credit Score Analysis:** An economist wants to determine the relationship between one's FICO score, \( x \), and the interest rate of a 36-month auto loan, \( y \). The given data represent the interest rate (in percent) a bank would offer on a 36-month auto loan for various FICO scores. | Credit Score, \( x \) | Interest Rate (percent), \( y \) | |-----------------------|----------------------------------| | 545 | 18.982 | | 595 | 17.967 | | 640 | 12.218 | | 675 | 8.612 | | 705 | 6.680 | | 750 | 5.150 | ### Tasks: a. **Find the least-squares regression line (Equation):** - Treat the FICO score, \( x \), as the explanatory variable and the interest rate, \( y \), as the response variable. b. **Determine the linear correlation coefficient** between compensation and stock return. - **Answer:** _______ c. **What type of linear relation exists between the two variables?** - **Answer:** _______ d. **Compute the coefficient of determination.** - **Answer:** _______ e. **Interpret the coefficient of determination.** - **Answer:** _______ f. **Draw a Scatter diagram of the data.** --- *For graph explanation:* - The **scatter diagram** would plot the FICO scores on the x-axis and the corresponding interest rates on the y-axis. Each point on the graph represents a pair of score and rate values. This visual representation can help identify patterns or the nature of the relationship between the two variables.
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