{"id":57,"date":"2017-07-28T22:24:20","date_gmt":"2017-07-28T22:24:20","guid":{"rendered":"http:\/\/depts.washington.edu\/sefsqel\/wordpress\/?page_id=57"},"modified":"2025-08-13T04:58:12","modified_gmt":"2025-08-13T04:58:12","slug":"teaching","status":"publish","type":"page","link":"https:\/\/depts.washington.edu\/sefsqel\/teaching\/","title":{"rendered":"Teaching"},"content":{"rendered":"\n<div class=\"wp-block-image\"><figure class=\"alignright\"><img loading=\"lazy\" width=\"300\" height=\"225\" src=\"http:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-300x225.jpg\" alt=\"\" class=\"wp-image-124\" srcset=\"https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-300x225.jpg 300w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-768x576.jpg 768w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-1024x768.jpg 1024w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-375x281.jpg 375w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-750x563.jpg 750w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-1140x855.jpg 1140w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/IMG_2563-108x81.jpg 108w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/figure><\/div>\n\n\n\n<p><span style=\"color: #000080;\"><strong>COURSES AT UNIVERSITY OF WASHINGTON<\/strong><\/span><br><span style=\"color: #000000;\"><strong>QSCI 381 &#8211; Introduction to Probability and Statistics (Spring 2016 &#8211; 2021, 2025)<\/strong><\/span><br><span style=\"color: #000000;\">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, &#8220;t&#8221; and &#8220;F&#8221; distributions.<\/span><\/p>\n\n\n\n<p><span style=\"color: #000000;\"><strong>QSCI\/ESRM 451 &#8211; Analytical Methods in Wildlife Science (Every Winter)<\/strong><br>The purpose of this course is to provide a foundation of techniques commonly used by wildlife biologists in data collection and analysis.&nbsp; The focus will be predominantly on parameter estimation of demographic rates of animal populations.&nbsp; For many students this will be one of your final courses in wildlife biology before you enter the profession or continue your studies in graduate school. In that context, the purpose of the course is to explore, and discuss in detail, quantitative methods needed to address conservation and management problems in the real world.<\/span><\/p>\n\n\n\n<p><span style=\"\"><font color=\"#000000\"><b>SEFS\/SAFS 557 &#8211; Demographic <\/b><\/font><\/span><strong><span style=\"color: #000000;\">Estimation and Modeling<\/span><\/strong><strong><span style=\"color: #000000;\"> (Even Winters; co-taught with Sarah Converse)<\/span><\/strong>   The objective of this course is to provide students with a comprehensive practicum for population analysis. The course will introduce students to advanced tools for analysis of populations using capture-recapture and other forms of observational data. We will introduce practical approaches to implementing mark-recapture models and will build up to implementation of integrated population models &nbsp;<\/p>\n\n\n\n<p> <strong><span style=\"color: #000000;\">SEFS 590 &#8211; Bayesian Modeling for Ecologists (W 2017, F 2018, W2025)<\/span><\/strong><br> A<span style=\"color: #000000;\">n introduction to Bayesian statistics including basics of probability and likelihood theory, simple and hierarchical Bayesian models, MCMC, and model checking and inference. Students will learn the foundations of Bayesian statistics and work on building models and analyzing ecological datasets from fisheries and wildlife.<\/span> <\/p>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container\">\n<p> <strong><span style=\"color: #000000;\">SEFS 521 <\/span> &#8211; Data Integration in Ecology (F 2020)<\/strong>   The objective of this course is to discuss current topics in data integration and analysis and to work on a solution for a data integration problem. &nbsp;Data integration, including Integrated Population Models, is increasingly used in ecology and wildlife research.&nbsp; We will read through current papers and work through the methods. All students will participate in a group project to dig deeper into a topic of their choice, practicing coding and model fitting.<\/p>\n\n\n\n<p><strong>QERM 597 &#8211; Graduate Seminar (S 2022, 2024)<\/strong>   This is a seminar based course where the topics are selected by the students. This course is geared towards graduate students in the Quantitative Ecology and Resource Management degree. <\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"alignleft\"><img loading=\"lazy\" width=\"300\" height=\"225\" src=\"http:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-300x225.jpg\" alt=\"\" class=\"wp-image-119\" srcset=\"https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-300x225.jpg 300w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-768x576.jpg 768w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-1024x768.jpg 1024w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-375x281.jpg 375w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-750x563.jpg 750w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-1140x855.jpg 1140w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2-108x81.jpg 108w, https:\/\/depts.washington.edu\/sefsqel\/wordpress\/wp-content\/uploads\/2017\/08\/humpbacktail2.jpg 1142w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/figure><\/div>\n\n\n\n<p><span style=\"color: #ff0000;\"><strong>PREVIOUS COURSES AT NCSU<\/strong><\/span><br><span style=\"color: #000000;\"><strong>FW 453\/553 &#8211; Principles of Wildlife Science&nbsp;<\/strong><\/span><br><span style=\"color: #000000;\">Principles and applications of population dynamics and biology to the management of terrestrial vertebrates. Predicting population levels, composition and growth rates with and without management constraints. Strategies for wildlife conservation, utilization, and enhancement. Laboratories stress the collection and analysis of data, and focus on learning to analyze data using R, a powerful programming language. This course is taught every year in the spring.<\/span><\/p>\n\n\n\n<p><strong><span style=\"color: #000000;\">ST 506 &#8211; Sampling Animal Populations; Co-taught with Ken Pollock<\/span><\/strong><br><span style=\"color: #000000;\">Statistical methods applicable to sampling of wildlife populations, including capture-recapture, removal, change in ratio, quadrant and line transect sampling. In addition to an emphasis on model assumptions and study design, we focus on data analysis in Program MARK and R. Students complete a research project based on their own data and\/or research needs. This course is currently being taught (Fall 2015).<\/span><\/p>\n\n\n\n<p><strong><span style=\"color: #000000;\">FW 595 &#8211; Introduction to Models for Binary Data in Ecology&nbsp;<\/span><\/strong><br><span style=\"color: #000000;\">This graduate level course will provide an introduction to model building based on binary data. The first part of the class will review (generalized) linear (mixed) models and their use in ecology. We will then explore more advanced hierarchical models for occupancy including dynamic and community based models. The class will cover some theory but will primarily focus on practical applications including model development and analysis using the programs R and JAGS.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>COURSES AT UNIVERSITY OF WASHINGTONQSCI 381 &#8211; Introduction to Probability and Statistics (Spring 2016 &#8211; 2021, 2025)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, &#8220;t&#8221; and &#8220;F&#8221; distributions. QSCI\/ESRM 451 &#8211; Analytical Methods in Wildlife Science (Every Winter)The purpose [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/pages\/57"}],"collection":[{"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/comments?post=57"}],"version-history":[{"count":16,"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/pages\/57\/revisions"}],"predecessor-version":[{"id":622,"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/pages\/57\/revisions\/622"}],"wp:attachment":[{"href":"https:\/\/depts.washington.edu\/sefsqel\/wp-json\/wp\/v2\/media?parent=57"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}