UW Bothell Course Descriptions
UW Tacoma Course Descriptions
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Q SCI 190 Quantitative Analysis for Environmental Science (5) NSc, RSN
Covers applications of precalculus techniques and concepts to environmental, ecological, biological, and natural resource problems stressing the formulation, solution, and interpretation of mathematical procedures. Cannot be taken if credit received for MATH 124. Prerequisite: minimum grade of 2.0 in MATH 098 or MATH 103, a score of 151-169 on the MPT-GS test, or a score of 145-163 on the MPT-AS test. Offered: A.
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Q SCI 256 Introduction to Data Science Methods for Environmental Sciences (4) RSN
Provides a practical and approachable introduction to data science methods, including computational approaches used by research in the earth, environmental, and conservation sciences. Introduces data science techniques and develops skill proficiency in using computing to manipulate and analyze data in the natural sciences. Course overlaps with: CSE 160. Offered: W.
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Q SCI 291 Calculus for Natural Systems I: Derivatives (5) NSc, RSN
Introduction to differential calculus, emphasizing development of basic skills. Examples promote understanding of mathematics and applications to modeling and solving biological problems. Topics include optimization and curve analysis. Cannot be taken for credit if student received a minimum grade of 2.0 or above in MATH 124 (or equivalent). Course overlaps with: MATH 112; B MATH 144; and TMATH 122. Prerequisite: either MATH 120, Q SCI 190, or a minimum score of 2 on the AP MATH test (AB or BC); recommended: completion of Department of Mathematics' Guided Self-Placement. Offered: AW.
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Q SCI 292 Calculus for Natural Systems II: Integrals (5) NSc, RSN
Introduction to integral calculus, emphasizing development of basic skills. Examples promote understanding of mathematics and applications to modeling and solving biological problems. Topics include areas under curves, volumes, and differential equations. Cannot be taken for credit if student received a minimum grade of 2.0 or above in MATH 125 (or equivalent). Prerequisite: either MATH 124, Q SCI 291, or a minimum score of 3 on the AP MATH test (AB or BC). Offered: WSp.
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Q SCI 381 Introduction to Probability and Statistics (5) NSc, RSN
Applications to biological and natural resource problems stressing the formulation and interpretation of statistical tests. Random variables, expectations, variances, binomial, hypergeometric, Poisson, normal, chi-square, "t" and "F" distributions. Course overlaps with: STMATH 341; STMATH 390; and TME 351. Prerequisite: either MATH 120, MATH 124, MATH 125, MATH 126, Q SCI 190, Q SCI 291, or a minimum score of 2 on the AP MATH test (AB or BC). Offered: AWSp.
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Q SCI 403 Introduction to Resampling Inference (4) NSc
Introduction to computer-intensive data analysis for experimental and observational studies in empirical sciences. Students design, program, carry out, and report applications of bootstrap resampling, rerandomization, and subsampling of cases. Experience programming in R is beneficial. Cannot be taken if credit received for STAT 503/QMETH 503. Prerequisite: either STAT 311, STAT 341, STAT 390, STAT 391, or Q SCI 381 and Q SCI 482. Offered: jointly with STAT 403; Sp.
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Q SCI 451 Analytical Methods in Wildlife Science (3) NSc
This course provides a foundation of techniques commonly used by wildlife biologists in data collection and analysis. Predominantly focused on parameter estimation of demographic rates of animal populations. This course will explore, and discuss in detail, quantitative methods needed to address conservation and management problems in the real world. Prerequisite: ESRM 351 and Q SCI 482. Offered: jointly with ESRM 451; W.
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Q SCI 454 Introduction to Quantitative Ecology (5) NSc
Examines concepts in ecological modeling focusing on the rationale, interpretation, and motivation for modeling in ecological sciences. Explores individual, population, and ecosystem-based models. Excel-based computer exercises, model building and interpretation, readings. Prerequisite: MATH 125, MATH 135, or Q SCI 292; and Q SCI 381 or STAT 311. Offered: jointly with FISH 454; A.
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Q SCI 458 Quantitative Conservation and Management (5) NSc
Introduces students to quantitative methods used in conservation and management to model changes in fish and wildlife populations. Includes age-structured models, interactions between humans and protected areas, extinction risk, and effects of alternative management strategies. Covers fitting models to data using maximum likelihood and Bayesian approaches, and increasing the programming skill of students by using the R programming language. Recommended: FISH 454/Q SCI 454 and familiarity with the R programming language. Offered: jointly with FISH 458; Sp.
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Q SCI 480 Sampling Theory for Biologists (3) NSc
Theory and applications of sampling finite populations including: simple random sampling, stratified random sampling, ratio estimates, regression estimates, systematic sampling, cluster sampling, sample size determinations, applications in fisheries and forestry. Other topics include sampling plant and animal populations, sampling distributions, estimation of parameters and statistical treatment of data. Prerequisite: Q SCI 482. Offered: jointly with STAT 480; W, odd years.
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Q SCI 482 Statistical Inference in Applied Research I: Hypothesis Testing and Estimation for Ecologists and Resource Managers (5) NSc
Analysis of variance and covariance; chi square tests; nonparametric procedures multiple and curvilinear regression; experimental design and power of tests. Application to biological problems. Use of computer programs in standard statistical problems. Prerequisite: either STAT 311 or Q SCI 381. Offered: AW.
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Q SCI 483 Statistical Inference in Applied Research II: Regression Analysis for Ecologists and Resource Managers (5) NSc
Analysis of linear regression models and introduction to nonlinear models. Model selection using generalized F-tests; residual analysis. Application to categorical, count, binomial, transformed variables. Introduction to matrix formation of regression models and applications. Prerequisite: Q SCI 482. Offered: Sp.
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Q SCI 486 Experimental Design (4) NSc
Emphasizes data modeling using structured means resulting from choice of experimental and treatment design. Examines experimental designs, including crossed, nested designs; block; split-plot designs; and covariance analysis. Also covers multiple comparisons, efficiency, power, sample size, and pseudo-replication. Prerequisite: Q SCI 482. Offered: jointly with STAT 486; W, even years.
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Q SCI 497 Special Topics in Quantitative Science (1-15, max. 15) NSc
Topics not normally offered in regular curriculum. Format ranges from seminar/discussion, formal lectures, laboratory or modeling work. Offered: AWSpS.
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Q SCI 498 Internship (1-15, max. 15) NSc
Internship experience with a public agency or private company, supervised and approved by a faculty member. Preparation of professional report reflecting on the experience is required. Offered: AWSpS.
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Q SCI 499 Research Experience (1-15, max. 15)
Special studies in quantitative ecology and resource management for which there is not sufficient demand to warrant the organization of regular courses. Credit/no-credit only.
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