{"id":484,"date":"2014-04-07T16:02:37","date_gmt":"2014-04-07T20:02:37","guid":{"rendered":"http:\/\/jenkins.cos.ucf.edu\/?page_id=484"},"modified":"2016-11-30T15:01:34","modified_gmt":"2016-11-30T20:01:34","slug":"pcb-6466","status":"publish","type":"page","link":"https:\/\/sciences.ucf.edu\/biology\/jenkins\/classes\/pcb-6466\/","title":{"rendered":"PCB 6466 – Methods in Experimental Ecology I"},"content":{"rendered":"

When & Where:<\/strong>\u00a0Mon & Wed, 1-2:20 in BIO Rm. 305<\/p>\n

Who:<\/strong> Dave Jenkins & Lina Sanchez<\/p>\n

Syllabus <\/strong>[pdf]<\/a><\/p>\n

Recorded lectures are\u00a0available on\u00a0<\/span>youtube<\/a><\/p>\n

copter data<\/a><\/p>\n

Schedule:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Week<\/p>\n<\/td>\n

\n

Videos etc. (before class)<\/b><\/p>\n<\/td>\n

\n

Reading (before class)<\/b><\/p>\n<\/td>\n

\n

In-Class Topics<\/p>\n<\/td>\n

\n

Assignments<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n

1 (22-24 Aug)<\/td>\n\n

Installing R & RStudio<\/a><\/u><\/span><\/p>\n

RStudio Orientation (youtube)<\/a><\/p>\n

swirlstats.com<\/p>\n

Plot: generic X-Y Plotting<\/a><\/u><\/span><\/p>\n<\/td>\n

\n

R passes SAS in scholarly use<\/a><\/p>\n

R is still hot and getting hotter<\/a><\/u><\/span><\/p>\n

Much ado about <\/a><\/u><\/span>p<\/em><\/a><\/u><\/span><\/p>\n

But stats are > <\/a><\/u><\/span>p<\/em><\/a><\/u><\/span><\/p>\n

Hector Ch. 1 <\/span><\/span>& Appendix<\/span><\/span><\/td>\n

Course overview & goals<\/p>\n

The new statistics<\/span><\/span><\/p>\n

Intro to <\/a>R & <\/a>RStudio<\/a><\/u><\/span><\/td>\n

Install software<\/p>\n

Make a plot in R. Any plot.<\/td>\n<\/tr>\n<\/tbody>\n

2 (29-31 Aug)<\/span><\/td>\nData basics (youtube)<\/a><\/span><\/p>\n

Handling data (youtube)<\/a><\/span><\/p>\n

dplyr overview<\/a><\/span><\/p>\n

dplyr lesson <\/a><\/u><\/span>1<\/a><\/u><\/span><\/u><\/p>\n

or<\/span><\/span> read it<\/a><\/u><\/span><\/p>\n

dplyr lesson 2<\/a><\/u><\/span><\/td>\n

Hypotheses <\/span><\/span>1<\/a><\/u><\/span> , <\/span>2<\/a><\/u><\/span> , <\/span>3<\/a><\/u><\/span><\/p>\n

Not just a theory<\/a><\/p>\n

Chamberlin (1890)<\/a><\/p>\n

Platt (1964)<\/a><\/u><\/span><\/p>\n

McGill et al. (2006) excerpt<\/a><\/u><\/span><\/p>\n

Ecology & strong inference<\/a><\/u><\/span><\/td>\n

Readings discussion<\/p>\n

Handling Data in R<\/a><\/p>\n

Baby names data (DB)<\/td>\n

Homework #1<\/a><\/p>\n

(Due 7\u00a0Sep)<\/td>\n<\/tr>\n<\/tbody>\n

3 (5-7 Sep)<\/td>\nLABOR DAY – – – –<\/b><\/p>\n

Exper. Designs I (youtube)<\/a>\u00a0<\/a><\/p>\n

Exper.Designs II (youtube)<\/a><\/td>\n

– – – –<\/p>\n

Quinn & Keough excerpt (DB)<\/p>\n

Aho et al (2014) (DB)<\/span><\/span><\/p>\n

Helicopter experiment<\/a><\/u><\/span><\/td>\n

– – – –<\/p>\n

Designing research for model selection\u00a0(DB)<\/td>\n

Homework #2<\/p>\n

(Due 12 Sep)<\/td>\n<\/tr>\n<\/tbody>\n

4 (12-14 Sep)<\/td>\nStudy design & model selection<\/td>\nHelicopter experiment<\/a><\/u><\/span><\/td>\nDesign & conduct helicopter expt.<\/td>\nHomework #3<\/p>\n

(Due 19 Sep)<\/td>\n<\/tr>\n<\/tbody>\n

5 (19-21 Sep)<\/td>\nGraphing A (youtube)<\/a><\/p>\n

Graphing B (youtube)<\/a><\/p>\n

Graphing C (youtube)<\/a><\/td>\n

Getting Started with Ch<\/a><\/u><\/span>arts in R<\/a><\/u><\/span><\/p>\n

Plot: generic X-Y Plotting<\/a><\/u><\/span><\/p>\n

ggplot2<\/a><\/u><\/span> & <\/span><\/span>cowplot<\/a>\u00a0&\u00a0<\/u><\/span>lattice<\/a><\/u><\/span><\/td>\n

Graphing lab I<\/a><\/p>\n

Graphing lab II<\/a><\/td>\n

Homework #4<\/a><\/p>\n

Silwood Weather data<\/a><\/p>\n

(Due 26 Sep)<\/td>\n<\/tr>\n<\/tbody>\n

6 (26-28 Sep)<\/td>\nProbability (youtube)<\/a><\/p>\n

Distributions (youtube)<\/a><\/td>\n

Testing parametric assumptions<\/a><\/p>\n

Homogeneity tests<\/a><\/p>\n

Co<\/a>unt data<\/a><\/td>\n

Testing Normality & Variance<\/a><\/p>\n

Transforming data<\/a><\/td>\n

Homework #5<\/a><\/p>\n

(Due 3 Oct)<\/p>\n

speciespH.txt<\/a><\/td>\n<\/tr>\n<\/tbody>\n

7 (3-5 Oct)<\/td>\nz- and t-tests (youtube)<\/a><\/p>\n

ANOVAs I (youtube)<\/a><\/td>\n

Hector (2015) Ch. 2 & 3<\/span><\/span><\/td>\nDoing t-tests<\/a><\/p>\n

NC births data<\/a><\/p>\n

Copter ANOVAs<\/a><\/td>\n

Homework #6<\/a><\/p>\n

Medley.txt<\/a><\/p>\n

barley.txt<\/a><\/p>\n

possum.txt<\/a><\/p>\n

(Due\u00a010\u00a0Oct)<\/td>\n<\/tr>\n<\/tbody>\n

8 (10-12 Oct)<\/td>\nANOVAs II (youtube)<\/a><\/p>\n

Model selection\u00a0 (w\/ AIC)<\/a><\/td>\n

Hector (2015) Ch. <\/span><\/span>6<\/span><\/span><\/p>\n

Anderson et al. (2000)<\/span> (DB)<\/span><\/span><\/p>\n

Anderson & Burnham (2002) <\/span><\/span>(<\/span><\/span>DB)<\/span><\/span><\/td>\n

ANOVAs II<\/a><\/p>\n

fishes data<\/a><\/p>\n

ants data<\/a><\/p>\n

ponds data<\/a><\/p>\n

yields data<\/a><\/p>\n

Readings discussion<\/p>\n

Using AICc<\/a><\/td>\n

Homework #7<\/a><\/p>\n

(Due 17\u00a0Oct)<\/p>\n

wheat.txt<\/a><\/p>\n

census.txt<\/a><\/p>\n

cancer.txt<\/a><\/p>\n

competition.txt<\/a><\/td>\n<\/tr>\n<\/tbody>\n

9 (17-19 Oct)<\/td>\nboxplot, SD, SE, or CI?<\/a><\/span><\/td>\nHector (2015) Ch. 5<\/span><\/td>\nCIs etc.<\/a><\/p>\n

Power Analysis<\/a><\/td>\n

Homework #8<\/a><\/p>\n

chickwts.txt<\/a><\/p>\n

Ipomopsis.txt<\/a><\/p>\n

(Due 25 Oct)<\/span><\/td>\n<\/tr>\n<\/tbody>\n

10 (24-26 Oct)<\/td>\nBivariate Regressions (youtube)<\/a><\/span><\/p>\n

SMA Regressions (youtube)<\/a><\/span><\/td>\n

Hector (2015) Ch.\u00a04<\/span><\/p>\n

Warton et al. (2002) (DB)<\/span><\/td>\n

Linear Regressions<\/a><\/p>\n

tancat.txt<\/a><\/p>\n

FLHg.txt<\/a><\/p>\n

SMA Regression<\/a><\/p>\n

PB data set (txt)<\/a><\/td>\n

Homework #9<\/a><\/p>\n

MLB batting 2010.txt<\/a><\/p>\n

fishing.txt<\/a><\/p>\n

(Due 31\u00a0Oct)<\/span><\/td>\n<\/tr>\n<\/tbody>\n

11 (31 Oct – 2<\/p>\n

Nov)<\/td>\n

ANCOVAs (youtube)<\/a><\/span><\/p>\n

Multiple Regressions (youtube)<\/a><\/span><\/td>\n

Hector (2015) Ch. 7<\/span><\/td>\nANCOVAs<\/a><\/p>\n

Multiple Regressions<\/a><\/td>\n

Homework #10<\/span><\/p>\n

(Due 7\u00a0Nov)<\/span><\/td>\n<\/tr>\n<\/tbody>\n

12 (7-9 Nov)<\/td>\nGeneralized Linear Models I\u00a0(youtube)<\/a><\/p>\n

GLMs II (youtube)<\/a><\/td>\n

[Hector (2015) Ch. 8, 9<\/span><\/td>\nGLMs I (DB)<\/a><\/p>\n

clusters.txt<\/a><\/p>\n

GLMs II<\/a><\/p>\n

amphib roadkill data<\/a><\/td>\n

Homework #11<\/a><\/p>\n

ozone data<\/a><\/p>\n

(Due 14\u00a0Nov)<\/span><\/td>\n<\/tr>\n<\/tbody>\n

13 (14-16 Nov)<\/span><\/td>\nIntro to mixed effects models (youtube)<\/a><\/span><\/td>\nHector (2015) Ch. 10<\/span><\/td>\nMixed-Effect ANOVAs<\/a><\/p>\n

plant data 06-15<\/a><\/p>\n

GLMMs<\/a> <\/span><\/td>\n

Homework #12<\/a><\/p>\n

carrots.txt<\/a><\/p>\n

(Due 28 Nov)<\/td>\n<\/tr>\n<\/tbody>\n

14 (21-23 Nov)<\/td>\nLogistic regressions<\/a><\/span><\/p>\n

THANKSGIVING
\n<\/b><\/span><\/td>\n

– – – –<\/b><\/span><\/p>\n

 <\/td>\n

Logistic Regressions<\/a><\/span><\/p>\n

islandbird data<\/a><\/td>\n

<\/td>\n<\/tr>\n<\/tbody>\n
15 (28-30 Nov)<\/td>\n– – – –
\n<\/b><\/span><\/td>\n		Review above<\/span><\/p>\n

 <\/td>\n

Practice 1<\/a><\/span><\/p>\n

FL bear hunt 2015<\/a><\/p>\n

Practice 2<\/a><\/p>\n

election data<\/a><\/p>\n

Cumulative Final Exam <\/b>to you<\/b> <\/b>30<\/b>th<\/b><\/sup><\/span> <\/b><\/p>\n

census data<\/a><\/p>\n

predator-prey data<\/a><\/td>\n

<\/td>\n<\/tr>\n<\/tbody>\n
16 (5-7 Dec)<\/td>\nFinals Week<\/b><\/td>\nFinals Week<\/b><\/td>\nFinals Week<\/b><\/td>\nFinal DUE 7th<\/b><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n