The Q SCI courses are a series of math and statistics classes designed for students in biology or ecology-related sciences. Q SCI 291, 292, and 381 meet math requirements for a variety of majors across the UW campus. In addition, they can be taken in support of a Quantitative Science minor for undergraduate students.
Q SCI 190 Quantitative Analysis for Environmental Science (5), Stephen Scherba Jr.
Covers applications of pre-calculus techniques and concepts to environmental, ecological, biological, and natural resource problems stressing the formulation, solution, and interpretation of mathematical procedures. 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. Not available for credit to students who have completed MATH 124. Or higher. Offered: A.
Q SCI 291 Analysis for Biologists I (5), Jay Johnson, Stephen Scherba Jr.
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. Prerequisite: either MATH 120, Q SCI 190, a minimum score of 2 on advanced placement test, or a score of 153-163 on MPT-AS placement test. Not available for credit to students who have completed MATH 124 with a 2.0 or higher. Offered: AWS.
Q SCI 292 Analysis for Biologists II (5), Jay Johnson, Andrew Berdahl
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. Prerequisite: minimum grade of.7 in either Q SCI 291 or MATH 124. Not available for credit to students who have completed MATH 125 with a 2.0 or higher Offered: WSpS.
Q SCI 381 Introduction to Probability and Statistics (5), Gordon Holtgrieve, Patrick Tobin, Beth Gardner
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. Prerequisite: either MATH 120, MATH 124, MATH 125, MATH 126, Q SCI 190, or Q SCI 291, or a minimum score of 2 on advanced placement test, or a score of 153-163 on the MPT-AS placement test. Offered: AWSpS.
Q SCI 403/STAT 403 Introduction to Resampling Inference (4), Yen-Chi Chen
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. Credit allowed for STAT 403 or STAT 503, but not both. Prerequisite: either STAT 311/ECON 311, STAT 341, STAT 390/MATH 390, STAT 481/ECON 481, or Q SCI 381 and Q SCI 482. Offered: jointly with STAT 403; Sp.
Q SCI 451 Analytical Methods in Wildlife Science (3), Beth Gardner
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 QSCI 482; Recommended: Prerequisite courses in Wildlife Research Techniques and Quantitative Science. Offered: jointly with ESRM 451; W.
Q SCI 454 Ecological Modeling (5), Tim Essington
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. Offered: jointly with FISH 454; W.
Q SCI 458 Modeling and Estimation in Conservation and Resource Management (4), Trevor Branch
Explores the use of models in the evaluation of alternative management policies for natural resources, including modeling approaches, fitting models to data, and evaluating alternative management policies. Emphasizes calculating risk of extinction, and design of biological reserves. Offered: jointly with FISH 458; Sp.
Q SCI 482 Statistical Inference in Applied Research I: Hypothesis Testing and Estimation for Ecologists and Resource Managers (5), Trevor Branch, Indroneil Ganguly
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.
Q SCI 483 Statistical Inference in Applied Research II: Regression Analysis for Ecologists and Resource Managers (5)
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.
Q SCI 497 Special Topics in Quantitative Science (1-15, max. 15)
Topics not normally offered in regular curriculum. Format ranges from seminar/discussion, formal lectures, laboratory or modeling work. Offered: Varies annually.
Q SCI 498 Internship (1-15, max. 15)
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.
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.