Methods in Experimental Ecology I (PCB 6466)

Course Information
  • Time: Mondays and Wednesdays (1:00-2:20)
  • Room: Bio 305
  • Instructor: Dave Jenkins, office = BIO 111B, email [david.jenkins AT ucf.edu] for help / meetings
  • TA: Leo Ohyama, office = BIO 309 or 111, email [leoohyama AT knights.ucf.edu] for help / meetings

Textbook: Hector. 2015. The New Statistics with R. Available FREE thru UCF Library (with your login) at:

http://ezproxy.net.ucf.edu/login?url=http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780198729051.001.0001/acprof-9780198729051

Syllabus

Recorded lectures are available on youtube

Resources

Description

Learn how to design, analyze and interpret experiments and quantitative observations. Introduction to modern statistical software and basic statistical methods needed to collect, organize and interpret data critically. For beginning graduate and senior undergraduate researchers, this course bridges between undergraduate stats and Methods II.

TENTATIVE SCHEDULE (subject to hurricanes, etc.)
Week Videos etc. (before class) Reading (before class) In-Class Topics Assignments
1 Installing R & RStudio

RStudio Orientation

swirlstats.com

Plot: generic X-Y Plotting

Popularity of stats software

Much ado about p

But stats are > p

Hector Ch. 1 & Appendix

Course overview & goals

The new statistics

Intro to R & RStudio

  1. Install R & RStudio.
  2. Make a plot in R. Any plot.
  3. Email it to Leo.
2 Data basics

Handling data

dplyr lesson 1

dplyr lesson 2

Hypotheses 1 , 2

Chamberlin (1890)

Platt (1964)

McGill etal (2006) excerpt

Ecology & strong inference

Hurlbert (1984)

Chaves (2010)

Readings discussion

Handling Data in R

SSA babynames

Homework #1

(Due 5 Sep)

3 MON: LABOR DAY

Experimental Designs 1

Experimental Designs 2

– – – –

Helicopter experiment

 

Designing Research for Model Selection

Homework #2

(Due 12 Sep)

4 How To Graph in RStudio: The Basics

ggplot 2, lecture #1

ggplot 2, lecture #2

Graphing in R ggplot2 #1

Graphing in R ggplot2 #2

Helicopter experiment

Tufte in R

Getting Started with Charts in R

Plot: generic X-Y Plotting

ggplot2 cheat sheet

cowplot, lattice

Conduct helicopter experiment

Your Copter Data v2

Graphing copter data I

Homework #3

Silwood weather data

(Due 19 Sep)

5 Probabilities

Distributions

Normality tests I

Normality tests II

Homogeneity tests

Do not log-transform count data

Graphing copter data II

Normality & Variance

Transforming Data

Homework #4

species pH data

(Due 26 Sep)

6 Z- and t-tests

ANOVAs I

Hector (2015) Ch. 2 & 3

t tests

NC births data

copter anovas I

Homework #5

zinc data

barley data

possum data

(Due 4 Oct)

7 ANOVAs II

Model selection (w/ AIC)

Hector (2015) Ch. 6

Anderson et al. (2000)

Anderson & Burnham (2002)

Aho et al. (2014)

Readings discussion

Copter ANOVAs II

Using AICc

Homework #6

wheat censusrb cancer

(Due 10 Oct)

8

Representing statistical variation

Hector (2015) Ch. 5

CIs

CIs.R (a txt file)

Power analysis

Homework #7

competition chickwts

(Due 17 Oct)

9 OLS Regressions

SMA Regressions

Hector (2015) Ch. 6

CIs, not posthoc power!

Warton et al. (2012)

Linear regressions

tancat   FLHg

SMA regression

PB

Homework #8

MLBbatting2010 fishery

(Due 24 Oct)

10 ANCOVAs

Multiple Regressions

Hector (2015) Ch. 7

ANCOVAs

ipomopsis

Multiple Regressions

Homework #9

timber2

(Due 2 Nov)

11 Generalized Linear Models I

Generalized Linear Models II

Hector (2015) Ch. 8, 9 GLMs 1

GLMs 2 & CART

ozone data

Homework #10

MLBbatting2010

(Due 10 Nov)

12

Intro to Mixed Effects Models

Hector (2015) Ch. 10

Mixed Effects ANOVAs

plantdata0615

Mixed Effects Regressions

Homework #11

carrots

(Due 16 Nov)

13 MON: VETERAN’S DAY

Logistic Regressions

 

Logistic Regressions

islandbird

Homework #12

parasites

(Due 21 Nov)

14 Mon: Intro to Multivariate Analyses

WED: T’GIVING

CRAN Multivariate Task View

NMDS in R

Ordination Overview

– – – –

Ordination

data

– – – –

no homework

 

– – – –

15

– – – –

– – – – Study design & analyses, revisited

Review & in-class practice

Cumulative Final Exam to you 28th

crowding

censusdata

predprey

no homework

– – – –

16

Finals Week

Finals Week  Finals Week

Final DUE 6th