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Week Date Lecture topic Lab topic Notes
1 M Jan. 6 Course Introduction
W Jan. 8 Introduction to Statistics Using R Markdown/Common Mathematical Notation
2 M Jan. 13 Probability Refresher
W Jan. 15 Probability Refresher Data simulation techniques
3 M Jan. 20 No class (MLK Day)
W Jan. 22 Snow Day! Snow Day (no Lab)
4 M Jan. 27 Principles of Bayesian Inference (Part 1)
W Jan. 29 Principles of Bayesian Inference (Part 2) Basic MCMC
5 M Feb. 3 Introduction to Linear Models and Nimble
W Feb. 5 Generalized Linear Model Review Regression analysis using Nimble
6 M Feb. 10 Informative Priors
W Feb. 12 Random Effects Choosing Priors
7 M Feb. 17 State Space Models
W Feb. 19 More State Space Models
8 M Feb. 24 N-mixture Models
W Feb. 26 Dynamic N-mixture Missing Data
9 M Mar. 3 Spring Break - No Class
W Mar. 5 Spring Break - No Class
10 M Mar. 10 Occupancy Models
W Mar. 12 Dynamic Occupancy Models Goodness of Fit tests
11 M Mar. 17 Simple Movement Models
W Mar. 19 More Movement Models Lab 8: RSFs
12 M Mar. 24 Simple CMR for Abundance
W Mar. 26 Closed SCR Lab 9: SCR
13 M Mar. 31 Known Fate
W Apr. 2 CJS Models Lab 10
14 M Apr. 7 Continuous Time CJS
W Apr. 9 Multi-state CMR Lab 11
15 M Apr. 14 TBD
W Apr. 16 TBD Lab 12
16 M Apr. 21 TBD
W Apr. 23 Lab 13
17 M Apr. 28