While the topics covered are broad, each week will feature different examples from genetics, ecology, molecular, and evolutionary biology highlighting uses of each individual set of techniques.

W&S = Whitlock and Schluter, G&W = Grolemund and Wickham, U/P for linked pdfs = biol607

**Lecture:** How do we use data to understand how the world works?

**Lab:** Intro to R. Matrices, Lists and Data Frames. Introduction to Markdown

**Reading:** G&W Preface, Intro, Workflow basics, Vectors, and Markdown Chapters, RMarkdown Cheat Sheet

**In Class Code:** R Intro Code from Lab

**Etherpad:** https://etherpad.wikimedia.org/p/607-intro

**Lecture:** Sampling and Simulation for Estimation. Descriptive statistics, and the creation of good observational sampling designs.

**Lab Topic:** Sampling and simulation. Libraries in R. Dplyr.

**Reading:** W&S 1,3-4, G&W Chapter 5, 11, 18, Dplyr cheat sheet

**Optional Reading:** Cumming et al. 2007 on SDs, SEs, and CIs, Simpler Coding with Pipes, Managing Data Frames with the Dplyr package

**Etherpad:** https://etherpad.wikimedia.org/p/sampling

**In Class Code:** Code from Lab

**Homework:** https://github.com/biol607/2016_homework_02_sampling

**Lecture:** Data visualization.

**Lab Topic:** Data import and introduction to ggplot2. Forcats and factors. Data for lab here.

**Reading:** W&S Chapter 2, Unwin 2008, G&W Chapters on Data Vizualization and Graphics for Communication, Ggplot2 cheat sheet

**Optional Reading:** Friendly 2008 on History of Data Viz

**Etherpad:** https://etherpad.wikimedia.org/p/dataviz

**In Class Code:** Loading Data, Intro to ggplot2

**Homework:** https://github.com/biol607/2016_homework_03_ggplot2

**Lecture:** Frequentist Hypothesis Testing, NHST, Z-Tests, and Power

**Lab Topic:** Distributions in R, Frequentist Hypothesis testing via simulation

**Reading:** W&S 5-7, G&W Chapter 7, 16, Abraham Lincoln and Confidence Intervals and links therein

**Etherpad:** https://etherpad.wikimedia.org/p/607-hypotheses

**In Class Code:** Distributions and Power

**Quiz:** http://tinyurl.com/hyp-pre-quiz

**In Class Code:** Distributions and Power

**Homework:** https://github.com/biol607/2016_homework_04_hypothesis_power

**Lecture:** T tests, χ2 tests, and p

**Lab Topic:** Statistical analysis functions for t and \(\chi^2\) in R, data

**Reading:** W&S 8-12, G&W Chapter 10, 20

**Discussion Reading:** ASA Statement on P-Values, And choose one of the accompanying rejoinders (sign up in here) (also feel free to read them all) **Additional Readings on P-Values**: Peaceful negotiation in the face of so-called ‘methodological terrorism’, P-value madness: A puzzle about the latest test ban (or ‘don’t ask, don’t tell’), The Paradox of Replication, and the vindication of the P-value (but she can go deeper)

**Etherpad**: https://etherpad.wikimedia.org/p/607-t_tests

**In Class Code:** t and chi square

**Lecture:** Least Squares Linear Regression: Correlation and Regression, Fit and Power

**Lab Topic:** Linear regression, diagnostics, visualization, and data

**Reading:** W&S 16-17, G&W on model basics, model building

**Etherpad:** https://etherpad.wikimedia.org/p/607-lm

**In Class Code:** lm

**Lecture:** Linear Model Power Analysis, Likelihood, Fitting a line with Likelihood

**Lab Topic:** Calculating and visualizing Likelihoods, fitting a line with bbmle

**Reading:** W&S 20, G&W Chapter Iteration

**Etherpad:** https://etherpad.wikimedia.org/p/607-likelihood

**In Class Code:** power analysis, linear models with likelihood

**Lecture:** Bayesian Inference, Fitting a line with Bayesian techniques

**Lab Topic:** Bayesian computation in R, Fitting a line with Bayesian techniques

**Reading:** Ellison 1996, Statistical Rethinking Chapter 1 and Chapter 2, R Users will Now Inevitably Become Bayesians

**Additional Reading on rstanarm**: How to use it, Linear Models in rstanarm, more vignettes, rstanarm and more, Bayesian basics with R

**Etherpad:** https://etherpad.wikimedia.org/p/607-bayes

**In Class Code:** Bayesian Data Analysis

**Lecture:** Joins, Tidy data

__Data:__ Hemlock

**Reading:** 10 Commandments for Good Data Managament, G&W Chapters on tidy data, Strings, and Dates

**Etherpad:** http://etherpad.wikimedia.org/p/607-tidy

**In Class Code:** Tidy, markdown options

**Lecture:** Experimental design and ANOVA part 1, part 2

**Lab Topic:** One-Way ANOVA, Midterm work session

**Reading:** W&S Chapter 14-15

**Etherpad:** https://etherpad.wikimedia.org/p/607-anova

**Lectures:** Experimental Design in a Multicausal World - Multiway ANOVA, Factorial ANOVA

**Lab Topic:** Discussion of Hurlbert, Factorial ANOVA

__Lab Data:__ Multiple Files

**Reading:** W&S 18, Hurlbert 1984, Cottingham et al. 2005

**In Class Code:** lots of anova

**Lecture:** The General Linear Model: ANCOVA, Multiple Regression, and Interaction Effects, Information Theoretic Approaches

**Lab Topic:** Multiple Regression, Multimodel Inference - data files

**Readings:** Symonds and Moussalli 2010

**Optional Readings:** The whole Ecology Special Section on P Values is incredible reading.

**Etherpad:** https://etherpad.wikimedia.org/p/607-mlr

**In Class Code:** ancova, mlr, and aic

**Lecture:** Entering a non-normal world - Modeling count data with Genearlized linear models. Overdispersed continuous data.

**Lab Topic:** Generalized Linear Models. Diagnostics with DHARMa.

**Reading:** O’Hara 2009 through section on GLMs, O’Hara and Kotze 2010, Wharton and Hui 2011, Hartig DHARMa vignette

**Lecture:** Class’s Choice

**Lab Topic:** Class’s Choice, Final Presentation Open Lab

**Lecture:** Final Presentations