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== Special Topics - Data Analysis and Acquisition - Tentative Outline ==
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'''Special Topics: Data Analysis and Acquisition'''
  
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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. The course number may be special topics, depending on whether CU can approve the new course number by then.
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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.
  
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* Introduction to computer graphing, functions and programming (Igor, 2 weeks)
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== Course Information ==
  
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* Basic Data Analysis (Igor, 6 weeks)
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* Lectures: Tue & Thur 12:30 pm - 1:45 pm, Ekeley W166
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* Office Hours: TBD
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* [https://docs.google.com/document/pub?id=1QZP2J30bkhKxIEtMxWJoRg3A3-YCZwMfWQs05YF6m1Y Course Syllabus]
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* Required Texts
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** Taylor, ''Error Analysis'', 2nd. Ed., 1997.  ISBN: 093570275X, on reserve at Norlin
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** Press, Teukolsky, Vetterling, and Flannery, ''Numerical Recipes''
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***[http://www.nr.com/oldverswitcher.html 2nd. Ed. free online]  You can read the version for any of the coding languages; we'll focus on the discussion, not the code.
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***[http://www.nr.com/aboutNR3electronic.html 3rd. Ed. available for purchase online] or book, 2007.  ISBN: 9780521884075, on reserve at Norlin.
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** Allen and Tildesley, ''Computer Simulation of Liquids'', 1987.  ''Selections will be posted here.''
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== Tentative Assignment Dates ==
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All assignments are due at the start of class.  All homeworks will include electronic submission of an Igor experiment file, and some may also include submission of written material in class.
 +
 
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* HW 1:  Tuesday, 9/11/2012
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* HW 2:  Thursday, 9/27/2012
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* HW 3:  Tuesday, 10/16/2012
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* '''Midterm Exam:  10/18/2012  (in class)''', on all of the "basic" techniques below
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* HW 4:  Tuesday, 11/6/2012
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* HW 5:  Thursday, 11/29/2012
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* HW 6:  ''Friday'', 12/14/2012
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* '''Final Exam: 12/19/2012,  1:30-4 pm''', cumulative, with emphasis on the latter half of the course; location TBD
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== Lectures, Reading, and Homework ==
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== Introduction to computer graphing, functions and programming (Igor, 2 weeks) ==
 +
 
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*Igor Resources
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** [[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.
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** [http://wavemetrics.com/products/igorpro/manual.htm Online version of the Igor User's Manual] that also has a link to the pdf version.
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*** pdf version also available inside Igor under Help
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* Homework Igor Resources
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**[http://cires.colorado.edu/jimenez-group/Chem-6111/Homework/Chem6111_HWexpTemplate_v2.pxt Igor Homework Template]
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*** Please use this for all of your homeworks!  Open it when you start each homework.  When you're ready to save your experiment, it will ask you to save in the regular experiment format, .pxp (packed experiment).  Do save it that way.  Don't overwrite the template file!
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**[http://cires.colorado.edu/jimenez-group/Chem-6111/Homework/IgorProgrammingConventions_v2.ipf Igor Programming Conventions]
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*** Save this file, then open it on your computer.  It will load into Igor (.ipf is Igor Procedure File).
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*[http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_082812_Introduction.pdf Lecture Notes: Course Intro]
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** ''Work through "Getting Started" in the Igor Manual
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*[http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_082812_SimpleLineFunction.pdf Lecture Notes: Simple Function]
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* [http://cires.colorado.edu/jimenez-group/Chem-6111/Homework/Chem6111_Fa12_HW1%20-%20Intro%20to%20Igor.pdf Homework 1], due Thursday, Sept. 6 at the beginning of class, in the d2l dropbox.
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 +
== Basic Data Analysis (Igor, 6 weeks) ==
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*''Reading for Tues, 9/4/12:  Taylor Ch. 1-4 (emphasis on 3 & 4)''
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* precision, uncertainty
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** Taylor Ch. 2
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* propagation of errors  (Taylor Ch. 3)
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**[http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_090412_ErrorPropFunction.pdf Lecture Notes: Error Propagation Function]
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**[http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_090612_ErrorPropWfor.pdf Lecture Notes: Error Propagation Function with for loop]
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* Statistics:
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** statistical parameters
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*** Avg, Std Dev, Pop Std Dev, SDOM
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**** Taylor Ch. 4
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**** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Taylor_Ch4.5_exampleData.itx  Example Data]
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**** NR Ch. 14
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* [https://docs.google.com/document/pub?id=1AZwxtwNL5arSlmXchuCIwK82DVPZwNQZPMx9tQh3zGE Homework 2], due Thursday, Sept. 13 at the beginning of class, in the d2l dropbox + paper
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*[http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_091112_GraphsIgorFiles.pdf Lecture Notes: Good graphs and Igor Files]
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* [http://onlinestatbook.com/stat_sim/sampling_dist/ Online sampling distribution tool]
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*[http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_091312_Sampling_UsingWaves.pdf Lecture Notes: Sampling Statistics and waves in Igor]
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* Histograms & number of bins
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** Igor manual
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** Taylor Ch. 5
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* Distributions
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** Gaussian (normal): Taylor Ch. 5
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** Binomial: Taylor Ch. 10
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** Poisson: Taylor Ch. 11
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*** Derivation of the Poisson distribution from the binomial distribution: [http://www.khanacademy.org/math/statistics/v/poisson-process-1 Kahn Academy - Part 1], [http://www.khanacademy.org/math/statistics/v/poisson-process-2 Kahn Academy  - Part 2]
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_091812_Normal_Binomial_Dist.pdf Lecture Notes: Normal and Binomial Distributions]
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_092012_Binomial_PoissonIntro.pdf Lecture Notes: Binomial & Poisson Distributions]
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_092512_Poisson2.pdf Lecture Notes: more Poisson Distributions]
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_092712_HypothTesting.pdf Lecture Notes: Hypothesis Testing]
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*[https://docs.google.com/document/pub?id=1JkJYMauwMhNbOx0HBFrgGLoM6h-psOjJ2xB7kFCdoEU Homework 3], due Tuesday, Sept. 27 at the beginning of class, in the d2l dropbox
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/Homework/ExamScores_3exams.itx Exam score data itx]
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* ANOVA
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** Zar, Bioanalytical Statistics
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_100212_ANOVA.pdf Lecture Notes: ANOVA]
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_100912_HistogramCodeReview.pdf Lecture Notes: Histogram Code Review]
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* Simple Linear Fits
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** vertical vs orthogonal distance regression
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** squared vs absolute value errors for regression
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** weighted vs unweighted regression
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_101112_FitToLine.pdf Lecture Notes: Linear Fits]
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*[https://docs.google.com/document/pub?id=1DRF9RrYnlsGavOXPvilIqGu5UU_m5qz5ekPl25wSuyk Homework 4], due Thursday, Oct. 18 at the beginning of class, in the d2l dropbox
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** [http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_101612_ExamReview_Graphs.pdf Lecture Notes: Midterm Exam Review]
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** Stat parameters NR Ch. 14
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* Fitting of custom functions
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** fitting known spectra to total spectrum
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** cubic spline fits
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** fixed x wave vs. free x wave
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* interpolation,
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* area integrals
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** NR Ch. 4
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** between markers
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** multidimensional data handling
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* Correlation and regressions (variants)
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*** Taylor Ch. 9
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*** NR Ch. 13.2, 14.5
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** centered (Pearson's) vs uncentered correlation
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*** NR Ch. 15.0-3
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* boxcar and weighted smoothing
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** Allen Ch. 6.5, NR Ch. 14.9
 
** propagation of errors
 
** propagation of errors
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** Basic analysis: interpolation, area integrals, multidimensional data handling
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* Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters (freq response in smoothing), low pass filters etc.
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** Statistics: calculating statistical parameters, distributions, precision, uncertainty, ANOVAA
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* Fitting of simple functions
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** Correlation and regressions (variants)
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** Taylor Ch. 8 (least squares)
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*** centered (Pearson's) vs uncentered correlation
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** chi2 Taylor Ch. 12
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*** vertical vs orthogonal distance regression
 
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*** squared vs absolute value errors for regression
 
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*** weighted vs unweighted regression
 
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** boxcar and weighted smoothing
 
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** Custom fitting of data
 
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* Advanced Data Analysis (Igor, 4 weeks)
 
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** convolution (student request to IMU)
 
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** Numerical solution of ODEs
 
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** Frequency analysis and FFT
 
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** Montecarlo simulations
 
  
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** Principal Component Analysis and Positive Matrix Factorization
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== Advanced Data Analysis (Igor, 4 weeks) ==
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* Numerical solution of ODEs
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**Euler's Method
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**[http://cires.colorado.edu/jimenez-group/Chem-6111/LectureNotes/Chem6111_Fa12_for102312_EulersMethod.pdf Pre-Lecture Notes: Euler's Method]
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** NR Ch. 17 (Runge-Kutta)  (NR 3rd ed. Ch. 17; 2nd ed. Ch 16; 1st ed. Ch 15)
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* convolution
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** NR Ch. 13.1
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* Montecarlo simulations
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** Allen Ch. 4, 7.3
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** NR Ch. 7.3, 7,7, 7.9, 15.8
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* Positive Matrix Factorization
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* Frequency analysis and FFT
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** Allen Ch. 6.3, 6.5
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** NR Ch. 12, 13
  
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* Data Acquisition (Labview, 3 weeks)
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== Data Acquisition (Labview, 3 weeks) ==
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** Fundamentals of data acquisition
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* Fundamentals of data acquisition
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** Data I/O, parsing of text files, write to file etc.
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* Data I/O, parsing of text files, write to file etc.
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** Labview: introduction and programming
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* Labview: introduction and programming
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** Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters, low pass filters etc.
 
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** Data acquisition problems brought by students from their research
 
  
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* Potential Texts
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== Additional Resources ==
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** Numerical Recipes (online)
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* Additional Texts
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** Building Scientific Apparatus (Moore, Davis, and Coplan)  
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** Building Scientific Apparatus (Moore, Davis, and Coplan)
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** Taylor Error Analysis
 
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** Stuff from Amber's stats class
 

Latest revision as of 11:16, 20 October 2012

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
  • Course Syllabus
  • Required Texts
    • Taylor, Error Analysis, 2nd. Ed., 1997. ISBN: 093570275X, on reserve at Norlin
    • Press, Teukolsky, Vetterling, and Flannery, Numerical Recipes
    • Allen and Tildesley, Computer Simulation of Liquids, 1987. Selections will be posted here.

Tentative Assignment Dates

All assignments are due at the start of class. All homeworks will include electronic submission of an Igor experiment file, and some may also include submission of written material in class.

  • HW 1: Tuesday, 9/11/2012
  • HW 2: Thursday, 9/27/2012
  • HW 3: Tuesday, 10/16/2012
  • Midterm Exam: 10/18/2012 (in class), on all of the "basic" techniques below
  • HW 4: Tuesday, 11/6/2012
  • HW 5: Thursday, 11/29/2012
  • HW 6: Friday, 12/14/2012
  • Final Exam: 12/19/2012, 1:30-4 pm, cumulative, with emphasis on the latter half of the course; location TBD

Lectures, Reading, and Homework

Introduction to computer graphing, functions and programming (Igor, 2 weeks)

  • Homework Igor Resources
    • Igor Homework Template
      • Please use this for all of your homeworks! Open it when you start each homework. When you're ready to save your experiment, it will ask you to save in the regular experiment format, .pxp (packed experiment). Do save it that way. Don't overwrite the template file!
    • Igor Programming Conventions
      • Save this file, then open it on your computer. It will load into Igor (.ipf is Igor Procedure File).
  • Homework 1, due Thursday, Sept. 6 at the beginning of class, in the d2l dropbox.

Basic Data Analysis (Igor, 6 weeks)

    • Stat parameters NR Ch. 14
  • Fitting of custom functions
    • fitting known spectra to total spectrum
    • cubic spline fits
    • fixed x wave vs. free x wave
  • interpolation,
  • area integrals
    • NR Ch. 4
    • between markers
    • multidimensional data handling
  • Correlation and regressions (variants)
      • Taylor Ch. 9
      • NR Ch. 13.2, 14.5
    • centered (Pearson's) vs uncentered correlation
      • NR Ch. 15.0-3
  • 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 simple functions
    • Taylor Ch. 8 (least squares)
    • chi2 Taylor Ch. 12

Advanced Data Analysis (Igor, 4 weeks)

  • Numerical solution of ODEs
  • convolution
    • NR Ch. 13.1
  • Montecarlo simulations
    • Allen Ch. 4, 7.3
    • NR Ch. 7.3, 7,7, 7.9, 15.8
  • Positive Matrix Factorization
  • Frequency analysis and FFT
    • Allen Ch. 6.3, 6.5
    • NR Ch. 12, 13

Data Acquisition (Labview, 3 weeks)

  • Fundamentals of data acquisition
  • Data I/O, parsing of text files, write to file etc.
  • Labview: introduction and programming

Additional Resources

  • Additional Texts
    • Building Scientific Apparatus (Moore, Davis, and Coplan)
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