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ENVS 202 - Data Analysis for Scientists |
A comprehensive study of how to use powerful statistical tools to prepare, analyze, interpret, and visualize data collected in the physical, biological and environmental sciences. Practical and applied analysis are emphasized using case studies and critical assessment of the use of statistical methods in published literature. Topics include design of experiments, univariate distributions, exploratory data analysis, inferential statistics and hypothesis testing, linear and generalized linear models, and time-series analysis, using the statistical computing and graphics software R. Non-parametric analyses and careful consideration of confidence intervals are emphasized.
Prerequisite: MATH 123 College Algebra or the eligibility to enroll in MATH 200 Precalculus.
1.000 Credit hours 4.000 Lecture hours Levels: Non-Matriculated, Undergraduate Schedule Types: Independent/Directed Study, Lecture Geography Department Course Attributes: Undergraduate Level Course Restrictions: May not be assigned one of the following Student Attributes: DGCE Student |
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