Supplement
Fitting Quadratic Models to Data
1
Docsity.com
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Guidelines and tips
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Fitting Quadratic Models to Data: Calculating Average Error, Slides of Engineering Physics
How to calculate the average error in fitting a quadratic model to data. The text defines the error as the difference between the actual and predicted values, and the sum of squared errors (sse) as the measure of the model's accuracy. An example with data points from 1950 to 2000 and calculates the average error for the quadratic model.
Typology: Slides
2012/2013
1 / 5
This page cannot be seen from the preview
Don't miss anything!
Related documents
Partial preview of the text
Download Fitting Quadratic Models to Data: Calculating Average Error and more Slides Engineering Physics in PDF only on Docsity!
Supplement
Fitting Quadratic Models to Data
Best Fit
n
SSE
Average Error =
2
• We have learned from previous sections that
the best fitting curve for any given data, is the
curve that gives the smallest average error.
Year t=Reference Time =Year - 1950
Actual Data
Predicted Value
Error= E
1950 0 8 10.543 -2.543 6.
1960 10 45 39.653 5.347 28.
1970 20 90 90.963 -.963 0.
1980 30 160 164.47 -4.47 19.
1990 40 262 260.18 1.820 3.
2000 50 378.09 SSE=
59.277 4
E^2
AverageError = =
5
- Therefore, the average error is: