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MATH 1801 Scientific Data Analysis 3.0 Credits

A non-Calculus based introduction to the fundamental principles and applications of statistics for scientific data analysis. Topics include data exploration, probability distributions, Central Limit Theorem, hypothesis testing, z, t and F tests, one-way analysis of variance, linear regression, and contingency table analysis. Programming statistical applications will be included.

College/Department: Arts and Sciences/Mathematics
Repeat Status: Not repeatable for credit
Prerequisites: MATH 1001 [Min Grade: C-] or MATH 1200 [Min Grade: C-] or APEM 70 or APC 70