Physics307L:Schedule/Week 10 agenda: Difference between revisions
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__NOTOC__ | |||
==Fitting a line== | |||
==AKA Linear Regression, least-squares fit for a line== | |||
===[[/Why linear fit|Why and when linear fit?]]=== | |||
===[[/Linear fit theory|Theoretical background]]=== | |||
===[[/Linear fit practice|Practical examples]]=== | |||
**Why fitting a line? | **Why fitting a line? | ||
***Linear relations & This versus 1/sqrt(that) (examples: e-diffraction; e/m lab) | ***Linear relations & This versus 1/sqrt(that) (examples: e-diffraction; e/m lab) | ||
Revision as of 03:03, 22 October 2007
Fitting a line
AKA Linear Regression, least-squares fit for a line
Why and when linear fit?
Theoretical background
Practical examples
- Why fitting a line?
- Linear relations & This versus 1/sqrt(that) (examples: e-diffraction; e/m lab)
- [math]\displaystyle{ y=Ae^{Bx} }[/math]
- Theoretical
- Assume gaussian distribution for each [math]\displaystyle{ y_i }[/math] with same sigma for all measurements (not necessary, but simplifies it).
- Maximum likelihood...Chi-squared
- Derivative (minimize Chi-squared) / solve
- Just show the answer, ... skip derivation for time for practical examples.
- Practical step by step w/ Excel..."R"...."Octave?"
- Why fitting a line?
