CHEM-6111

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
• Basic analysis: interpolation, area integrals, multidimensional data handling
• Statistics: calculating statistical parameters, distributions, precision, uncertainty, ANOVAA
• Correlation and regressions (variants)
  • centered (Pearson's) vs uncentered correlation
  • vertical vs orthogonal distance regression
  • squared vs absolute value errors for regression
  • weighted vs unweighted regression
• boxcar and weighted smoothing
• Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters, low pass filters etc.
• Fitting of custom functions

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)