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exponential function

exponential function

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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Use exponential regression to find an exponential function that best fits these data. Round all values to the hundredths. 
f(x)=  

Use linear regression to find a linear function that best fits these data.  Round all values to the hundredths.
g(x)=

The educational material presents a table of data points with two columns labeled "x" and "y". The values are as follows: - x: 1, 2, 3, 4, 5, 6 - y: 697, 740, 755, 710, 769, 723 The instructions require finding a mathematical function that fits these data points using both exponential and linear regression techniques. 1. **Exponential Regression**: - Objective: Find an exponential function \( f(x) \) that best fits the data. - Requirement: Round all results to the nearest hundredth. - Placeholder is provided for \( f(x) = \) to enter the exponential equation. 2. **Linear Regression**: - Objective: Determine a linear function \( g(x) \) that best fits the data. - Requirement: Round all values to the nearest hundredth. - Placeholder is provided for \( g(x) = \) to enter the linear equation. 3. **Comparison**: - Question posed: Of the two equations (exponential or linear), which better fits the data? - Options include a radio button selection for "Exponential" or "Linear", with "Linear" selected. 4. **Action**: - A "Submit Question" button is available for user interaction. This content is designed to teach the application of regression analysis for data fitting and to determine which model provides the best fit for a given set of data points.
Transcribed Image Text:The educational material presents a table of data points with two columns labeled "x" and "y". The values are as follows: - x: 1, 2, 3, 4, 5, 6 - y: 697, 740, 755, 710, 769, 723 The instructions require finding a mathematical function that fits these data points using both exponential and linear regression techniques. 1. **Exponential Regression**: - Objective: Find an exponential function \( f(x) \) that best fits the data. - Requirement: Round all results to the nearest hundredth. - Placeholder is provided for \( f(x) = \) to enter the exponential equation. 2. **Linear Regression**: - Objective: Determine a linear function \( g(x) \) that best fits the data. - Requirement: Round all values to the nearest hundredth. - Placeholder is provided for \( g(x) = \) to enter the linear equation. 3. **Comparison**: - Question posed: Of the two equations (exponential or linear), which better fits the data? - Options include a radio button selection for "Exponential" or "Linear", with "Linear" selected. 4. **Action**: - A "Submit Question" button is available for user interaction. This content is designed to teach the application of regression analysis for data fitting and to determine which model provides the best fit for a given set of data points.
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