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Course Criteria
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3.00 Credits
Supervised individual research on a literary, linguistic, or cultural problem, culminating in a written thesis of fifty to eighty typewritten pages. Conference course for two semesters. Prerequisite: For 679HA, upper-division standing, admission to the Spanish Honors Program, and consent of the honors adviser; for 679HB, Spanish 679HA.
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3.00 Credits
Same as Chemistry 339J. Covers enzynmatic reaction mechanisms and how they can be manipulated using tools both from chemistry and molecular biology. Includes the study of enzymatic reaction mechanisms and the engineering of metabolic pathways and organisms. Course is designed for students pursuing careers in pharmaceutical and biotechnology careers. Three lecture hours a week for one semester. Prerequisite: Chemistry 310M, 318M, 320M, or 328M with a grade of at least C-.
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3.00 Credits
Emphasis on understanding the methods used to gather and analyze a variety of systems level data, including genomics, proteomics, and metabolomics. Developing and testing network models of systems level data. Three lecture hours a week for one semester. Prerequisite: Chemistry 339K with a grade of at least B; Computer Science 303E or 312 with a grade of at least C-; and Statistics and Scientific Computation 321 with a grade of at least C-.
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3.00 Credits
Same as Chemistry 364C. Restricted to biochemistry majors. Topics include physical methods for the study of macromolecules; chemistry of proteins; enzyme chemistry; regulatory mechanisms for gene expression; protein-nucleic acid interactions. Three lecture hours a week for one semester. Prerequisite: Chemistry 339K with a grade of at least B, Computer Science 303E or 312 with a grade of at least C-, and Statistics and Scientific Computation 321 with a grade of at least C-.
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3.00 Credits
For each semester hour of credit earned, one lecture hour a week for one semester. May be repeated for credit when the topics vary.
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3.00 Credits
Introduction to the use of statistical or mathematical applications for data analysis. Two lecture hours a week for eight weeks. Offered on the pass/fail basis only. May be repeated for credit when the topics vary. Offered on the pass/fail basis only. Prerequisite: Varies with the topic and is given in the Course Schedule.
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3.00 Credits
Students work on an individual research project under the supervision of one or more faculty members. For each semester hour of credit earned, the equivalent of one lecture hour a week for one semester. May be repeated for credit. Prerequisite: Upper-division standing and consent of instructor.
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3.00 Credits
Introduction to programming using both the C and Fortran (95/2003) languages, with applications to basic scientific problems. Covers common data types and structures, control structures, algorithms, performance measurement, and interoperability. Two lecture hours a week for one semester. Statistics and Scientific Computation 222 and 292 may not both be counted. Prerequisite: Credit or registration for Mathematics 408C, 408K, or 408N.
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3.00 Credits
Basic probability and data analysis for the sciences. Subjects include randomness, sampling, distributions, probability models, inference, regression, and nonlinear curve fitting. Three lecture hours and one discussion hour a week for one semester. May not be counted by students with credit for Educational Psychology 371, Mathematics 316, Statistics and Scientific Computation 303, 304, 305, or 306. Prerequisite: A score of at least 30 on the ALEKS placement examination.
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3.00 Credits
An introduction to the fundamental concepts and methods of statistics, with emphasis on applications in experimental science. Includes exploratory data analysis, correlation and regression, descriptive statistics, sampling distributions, confidence intervals, and hypothesis testing. Three lecture hours a week for one semester. Only one of the following may be counted: Mathematics 316, Statistics and Scientific Computation 303, 304, 305, 306. Prerequisite: A score of at least 30 on the ALEKS placement examination.
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