Which equation is a quadratic model for the data set? Hint: Use a graphing calculator or a spreadsheet program. Variable x Variable y 6 28 9 5 12 15 16 8 95 32 131 210 270 63 Oy=11.6018.1.2207² Oy=20.93302-93.8918 Oy=1.2246x² -5.0511r+24. 2880 Oy=1.155621.9375
Which equation is a quadratic model for the data set? Hint: Use a graphing calculator or a spreadsheet program. Variable x Variable y 6 28 9 5 12 15 16 8 95 32 131 210 270 63 Oy=11.6018.1.2207² Oy=20.93302-93.8918 Oy=1.2246x² -5.0511r+24. 2880 Oy=1.155621.9375
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Transcribed Image Text:Title: Determining a Quadratic Model for a Data Set
Introduction:
When analyzing a set of data, identifying the correct mathematical model can be essential for accurate predictions and understanding. A quadratic model is one option when relationships between variables are not linear.
Data Set:
The given data set includes two variables, x and y:
- Variable x: 6, 9, 5, 12, 15, 16, 8
- Variable y: 28, 95, 32, 131, 210, 270, 63
Objective:
Determine which equation represents a quadratic model for the data set provided.
Equations:
Here are the potential equations to consider:
1. \( y = 11.6018 - 1.2207x \)
2. \( y = 20.9330x - 93.8918 \)
3. \( y = 1.2246x^2 - 5.0511x + 24.2880 \)
4. \( y = 1.1556x^{1.9375} \)
Hint: Use a graphing calculator or a spreadsheet program to fit the equations and identify the quadratic model from the choices.
Conclusion:
Selecting the appropriate equation involves testing each against the data set to identify which provides the closest fit, confirming the relationship type, and ultimately understanding the behavior of the data through the identified model.
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