This is a graduate level chemistry course on data acquisition and analysis in chemistry. The topics covered in the course include statistical distributions of error, modeling of data, Fourier transform methods, and digital acquisition of data.

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## Syllabus

- Statistical Descriptions of Data
- Characterizing Experimental Distributions
- Theoretical Distributions
- Confidence Limits
- Hypothesis testing

- Modeling of Data
- Maximum Likelihood Estimators
- Linear Models
- Non-Linear Models
- Chi-squared minimization techniques
- The Simplex Method
- The Marquardt Method
- Extracting Confidence Limits for Model Parameters

- Fourier transform techniques
- Fourier Transform pairs
- FT Theorems - Similarity, Addition, Shift, Convolution
- Digital Fast Fourier Transform
- Multi-channel Spectrometry and the Fourier Transform

- Characteristics of analog and digital
data acquisition
- A/D conversion, Sampling theorem
- Signal averaging
- Filtering and smoothing

## Objectives

This course is intended to familiarize graduate students with modern approaches for the acquisition and treatment of information obtained from chemical systems.## Required Texts

None## Suggested Texts

*Statistics*, by R. J. Barlow

*Data Reduction and Error Analysis for the Physical Sciences*, Bevington and Robinson

*Numerical Recipes, 2nd Ed.*, Press, Teukolsky, Vetterling, and Flannery

*C, A Programming Language*, Kernighan and Ritchie

*Statistical Treatment of Experimental Data*, Young

## Prerequisites

There are few prerequisites needed for this course. Undergraduate level calculus and linear algebra should be adequate preparation. Some of the homework will involve writing computer programs.## Homework

All Homework must be turned in to be graded. Some of the homework will involve writing computer programs in C. Hard and soft copies of both code and output must be turned in for grading. Computers and compilers are available via ID card access in Room 2105 Newmann-Wolfrom.## Grading

Midterm Exam | 35% |

Homework | 30% |

Final Exam | 35% |