Lab 1
Complex Data Fitting by Least Squares Analysis
1/20/2012
Brian Wilhelm
 Excel/Results/Appendix
Brian Cosey Introduction/Write Up
David BonsaverDiscussion/Conclusion
Abstract
In this first lab data fitting was explored using a decaying wave function illustrated by a
Styrofoam ball on a string oscillating before a sensor. The wave function was then analyzed
using Logger Pro and Microsoft Excel in order to understand how to best fit data and decrease
error between theoretical and experimental by using computational and mathematical mean.
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View Full DocumentThree methods of curvefitting were utilized in this experiment: manual, RMS, and the program
Solver in Excel.
Results showed that the data from the experiment matched up well with known
mathematical equations, although discrepancies were present likely due to the oscillation of the
ball not being perpendicular to the plane of the sensor.
Introduction
In the first lab the topic was curvefitting procedures for data governed by mathematical
expressions more complex than simple straight lines, and simple exponential decay.
This
involved taking data captured from a harmonic moving ball whose motion was described by the
formula for damped oscillations:
The data was pasted into Excel and fitting a line with as little error as possible to the raw data
using tools found in excel and mathematical methods such as the root mean square method
shown in the equation below:
The overall goal of the lab was to learn how to use excel to improve our data collection methods
and overall quality of the experiment.
Procedure
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 Spring '08
 Treacy
 Least Squares, Regression Analysis

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