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: Fede Borghesi office = BIO 111, email [flopezborghesi 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:

Aug 26, 28

Installing R & RStudio

RStudio Orientation

swirlstats.com

Plot: generic X-Y Plotting

Popularity of stats software

Douglas Adams was right

Much ado about p

But stats are > p

Lederer et al. (2018)

Hector Ch. 1 & Appendix

Course overview & goals

The new statistics

Intro to R & RStudio

swirl

data carpentry

data carpentry – uf workshop

  1. Install R & RStudio.
  2. Make a plot in R. Any plot.
  3. Email it to Fede
2:

Sep 4

 

 

MON: LABOR DAY

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)

DORIAN !

3:

Sep 9, 11

Experimental Designs 1

Experimental Designs 2

Helicopter experiment

 

Last week’s Readings discussion

Designing Research for Model Selection

Design helicopter experiment

Handling Data in R

SSA babynames

Homework #1

(Due 16 Sep)

4:

Sep 16, 18

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

Conduct helicopter experiment

Our copter data

Graphing I

Homework #2

(Due 23 Sep)

5:

Sep 23, 25

Probabilities

Distributions

Normality tests I

Normality tests II

Homogeneity tests

Do not log-transform count data

Graphing II

Normality & Variance

Transforming Data

Homework #3

Silwood weather data

species pH data

(Due 30 Sep)

6:

Sep 30, Oct 1

Z- and t-tests

ANOVAs I

Hector (2015) Ch. 2 & 3

t tests

NC births data

Copter ANOVAs 1

Homework #4

zinc data

barley data

possum data

(Due 7 Oct)

7:

Oct 7, 9

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 2

Using AIC

Homework #5

wheat data

censusrb data

cancer data

(Due 14 Oct)

8:

Oct 14, 16

Representing statistical variation

Hector (2015) Ch. 5

Min. N for regressions

CIs

CIs.R (a txt file)

Power analysis

Homework #6

chickwts ipomopsis

(Due 21 Oct)

9:

Oct 21, 23

OLS Regressions

SMA Regressions

Hector (2015) Ch. 6

CIs, not posthoc power!

Warton et al. (2012)

Linear regressions

tancat   FLHg

SMA regression

PB

Homework #7

MLBbatting2010 fishery

(Due 28 Oct)

10:

Oct 28, 30

ANCOVAs

Multiple Regressions

Hector (2015) Ch. 7

ANCOVAs

ipomopsis

Multiple Regressions

Homework #8

timber2

(Due 4 Nov)

11:

Nov 4, 6

Generalized Linear Models I

Generalized Linear Models II

Hector (2015) Ch. 8, 9 GLMs 1

GLMs 2 & CART

ozone data

Homework #9

MLBbatting2010

(Due 11 Nov)

12:

Nov 11, 13

 

MON: VETERAN’S DAY

Intro to Mixed Effects Models

Hector (2015) Ch. 10

Mixed Effects ANOVAs

plantdata0615

Mixed Effects Regressions

Homework #10

carrots

(Due 18 Nov)

13:

Nov 18, 20

 

Logistic Regressions

 

Logistic Regressions

islandbird

Homework #11

parasites

(Due 25 Nov)

14:

Nov 25

Mon: Intro to Multivariate Analyses

WED: T’GIVING

CRAN Multivariate Task View

NMDS in R

Ordination Overview

ordinations.R.txt

diplo2017

– – – –

no homework

15

Dec 2

– – – –

NO CLASS WED.

– – – – Study design & analyses, revisited

Review & in-class practice

crowding

predprey

Cumulative Final Exam to you 2nd

no homework

– – – –

16

Finals Week

Finals Week  Finals Week

Final DUE MON DEC 9th