Methods in Experimental Ecology I (PCB 6466)

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

R 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.

REVISED Schedule (Thanks, Irma):
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 , 3

Chamberlin (1890)

Platt (1964)

McGill etal (2006) excerpt

Ecology & strong inference

Readings discussion

SSA babynames

Handling Data in R

Homework #1

(Due 6 Sep)

3 MON: LABOR DAY

Experimental Designs 1

Experimental Designs 2

– – – –

Helicopter experiment

 

– – – –

Designing Research for Model Selection

Homework #2

(Due 20 Sep) 

4 IRMA ! IRMA ! IRMA !

IRMA !

5 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

Tufte in R

Getting Started with Charts in R

Plot: generic X-Y Plotting

ggplot2 cheat sheet

cowplot, lattice

Copter data F16

Graphing copter data I

Homework #4

(Due 25 Sep)

Silwood Weather Data

6 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 5

species pH data

(Due 2 Oct)

7 Z- and t-tests

ANOVAs I

Hector (2015) Ch. 2 & 3

t tests

NC births data

Copter ANOVAs 1

Homework #6

barley  zinc possums

(Due 9 Oct)

8 ANOVAs II

Model selection (w/ AIC)

Hector (2015) Ch. 6

Anderson et al. (2000)

Anderson & Burnham (2002)

Aho et al. (2014)

Readings discussion

Copter ANOVA 2

Using AIC

Homework #7

wheat censusrb cancer

(Due 16 Oct)

9

Representing statistical variation

Hector (2015) Ch. 5

CIs

CIs.R (a txt file)

Power analysis

Homework #8

competition chickwts

(Due 23 Oct)

10 OLS Regressions

SMA Regressions

Hector (2015) Ch. 6

CIs, not posthoc power!

Warton et al. (2012)

Linear regressions

SMA regression

Homework #9

(Due 30 Oct)

11 ANCOVAs

Multiple Regressions

Hector (2015) Ch. 7

ANCOVAs

Multiple regressions

Homework #10

(Due 6 Nov)

12 Generalized Linear Models I

Generalized Linear Models II

Hector (2015) Ch. 8, 9 

GLMs I

GLMs II

Homework #11

(Due 13 Nov)

13

Intro to Mixed Effects Models

Hector (2015) Ch. 10

Mixed-effect ANOVAs

GLMMs

Homework #12

(Due 20 Nov)

14 Logistic Regressions

WED: THANKSGIVING

– – – – Logistic regressions

– – – –

– – – –

15

– – – –

– – – – Study design & analyses, revisited

Review & in-class practice

Cumulative Final Exam to you 29th

– – – –

16

Finals Week

Finals Week  Finals Week

Final DUE 6th