Difference between revisions of "CHEM-6111"
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=== Basic Data Analysis (Igor, 6 weeks) === | === Basic Data Analysis (Igor, 6 weeks) === | ||
* propagation of errors | * propagation of errors | ||
| − | * | + | ** Taylor Ch. 3 |
| − | * Statistics: calculating statistical parameters, | + | * interpolation, |
| + | * area integrals | ||
| + | ** NR Ch. 4 | ||
| + | ** between markers | ||
| + | ** multidimensional data handling | ||
| + | * Statistics: | ||
| + | ** calculating statistical parameters | ||
| + | ** distributions | ||
| + | *** Taylor Ch. 5 (normal), 10 (binomial), 11 (Poisson) | ||
| + | ** precision, uncertainty | ||
| + | *** Taylor Ch. 2 | ||
| + | ** ANOVA | ||
| + | *** Stat parameters NR Ch. 14 | ||
* Correlation and regressions (variants) | * Correlation and regressions (variants) | ||
| + | *** Taylor Ch. 9 | ||
| + | *** NR Ch. 13.2, 14.5 | ||
** centered (Pearson's) vs uncentered correlation | ** centered (Pearson's) vs uncentered correlation | ||
| + | *** NR Ch. 15.0-3 | ||
** vertical vs orthogonal distance regression | ** vertical vs orthogonal distance regression | ||
** squared vs absolute value errors for regression | ** squared vs absolute value errors for regression | ||
| + | *** chi2 Taylor Ch. 12 | ||
** weighted vs unweighted regression | ** weighted vs unweighted regression | ||
* boxcar and weighted smoothing | * boxcar and weighted smoothing | ||
| + | ** Allen Ch. 6.5, NR Ch. 14.9 | ||
** propagation of errors | ** propagation of errors | ||
| − | * Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters, low pass filters etc. | + | * Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters (freq response in smoothing), low pass filters etc. |
* Fitting of custom functions | * Fitting of custom functions | ||
| + | ** fitting known spectra to total spectrum | ||
| + | ** cubic spline fits | ||
| + | ** fixed x wave vs. free x wave | ||
=== Advanced Data Analysis (Igor, 4 weeks) === | === Advanced Data Analysis (Igor, 4 weeks) === | ||
Revision as of 13:20, 20 August 2012
Contents
CHEM 6111 - Special Topics - Data Analysis and Acquisition
This 3-credit course will be offered by Dr. Ingrid Ulbrich (with assistance from Prof. Jose L. Jimenez) in Fall of 2012. It will be a required course for 1st year analytical chemistry students, and optional for others.
Course Information
- Lectures: Tue & Thur 12:30 pm - 1:45 pm, Ekeley W166
- Office Hours: TBD
- Required Texts
- Taylor, Error Analysis, 2nd. Ed., 1997. ISBN: 093570275X, on reserve at Norlin
- Press, Teukolsky, Vetterling, and Flannery, Numerical Recipes
- 2nd. Ed. free online You can read the version for any of the coding languages; we'll focus on the discussion, not the code.
- 3rd. Ed. available for purchase online or book, 2007. ISBN: 9780521884075, on reserve at Norlin.
- Allen and Tildesley, Computer Simulation of Liquids, 1987. Selections will be posted here.
Lectures, Reading, and Homework
Introduction to computer graphing, functions and programming (Igor, 2 weeks)
- Igor Resources
- Igor_Quick_Reference. A page in the wiki with most of the the commands that are introduced in Getting Started, but aren't easy to find there.
- Online version of the Igor User's Manual that also has a link to the pdf version.
- pdf version also available inside Igor under Help
Basic Data Analysis (Igor, 6 weeks)
- propagation of errors
- Taylor Ch. 3
- interpolation,
- area integrals
- NR Ch. 4
- between markers
- multidimensional data handling
- Statistics:
- calculating statistical parameters
- distributions
- Taylor Ch. 5 (normal), 10 (binomial), 11 (Poisson)
- precision, uncertainty
- Taylor Ch. 2
- ANOVA
- Stat parameters NR Ch. 14
- Correlation and regressions (variants)
- Taylor Ch. 9
- NR Ch. 13.2, 14.5
- centered (Pearson's) vs uncentered correlation
- NR Ch. 15.0-3
- vertical vs orthogonal distance regression
- squared vs absolute value errors for regression
- chi2 Taylor Ch. 12
- weighted vs unweighted regression
- boxcar and weighted smoothing
- Allen Ch. 6.5, NR Ch. 14.9
- propagation of errors
- Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters (freq response in smoothing), low pass filters etc.
- Fitting of custom functions
- fitting known spectra to total spectrum
- cubic spline fits
- fixed x wave vs. free x wave
Advanced Data Analysis (Igor, 4 weeks)
- Numerical solution of ODEs
- convolution (student request to IMU)
- Montecarlo simulations
- Positive Matrix Factorization
- Frequency analysis and FFT
Data Acquisition (Labview, 3 weeks)
- Fundamentals of data acquisition
- Data I/O, parsing of text files, write to file etc.
- Labview: introduction and programming
- Data acquisition problems brought by students from their research
Additional Resources
- Additional Texts
- Building Scientific Apparatus (Moore, Davis, and Coplan)
