## Recently Published ##### for() loops in R
Basic for loop examples, and debugging them using functions. Also an example of using them to run multiple regressions. ##### Regression Data cleaning: Skibiel et al 2013 milk data
Data set up for Skibiel et al 2013. Journal of Animal Ecology. The evolution of the nutrient composition of mammalian milks ##### Class 2: Intro to R objects and lists
A very basic look at R objects, lists, and how to use them when plotting results of statistical tests. ##### plot.means(): plot means and 95%CIs
Simple function that plots means as individual points (not bars) & approx. 95% confidence intervals using user-supplied means & standard errors. (It can also take pre-calculated CIs). It provides some feed back via the console & on the plot itself regarding errors and how to make the plot more polished. ##### plotTukeysHSD(): Plot effect sizes from TukeyHSD object
Takes the output from R's TukeyHSD function for post-hoc comparisons & makes a prettier plot of the output than the default. ##### binom.CI(): function to calculate confidence intervals for binomial data
Implements Wilson's confidence interval for binomial proportions, such as number of deaths out of number of organisms in a toxicology experiment. ##### Lecture 29: Reporting results of 1-way ANOVA for your independent project
Lion data is re-formatted for use as a 1-way ANOVA to illustrate how to report results for you independent project. ##### Final Lab: Regression diagnostics, outliers transformation & x^2 terms
The goal of this lab is to: * Review assumptions of ANOVA/t-tests/regression * Review diagnostics plots for normality and constant variance * Introduce diagnostics plots for outliers * Investigate the role of transformation on diagnostic plots * Introduce how to model curved (non-linear) data with x^2 terms ##### Independent Project: Diagnostics for 2-sample t-test
Shows how to do diagnostics for a 2-sample t-test. Uses reformated lion data as an example. ##### Independent Project: Sample Paper Using Lion Data
An example of how to format analyses & plots for a scientific paper, using data on the relationship between the amount of pigment on lion snouts & their age from Whitman et al (2004). These data are featured in Ch 17 of Whitlock & Shulter’s Analysis of Bio Data, 2nd ed. The original data was presented in Whitman et al. Sustainable trophy hunting of African lions. Nature. ##### Plotting stuff over time: spagetti plots with interaction.plot()
This is a good function when the x axis is time and you are plotting a seperate line for each thing that is changing over time (the mean of a group, observations for individuals) ##### Final Lecture: Two-way ANOVA example with lions
Very brief introduction to 2-way ANOVA (aka factorial ANOVA). The lion data is set up to do this. ##### Final Lecture: 1-way ANOVA with Lions Data
How to write up results for you independet project if you are doing a 1-way ANOVA. The lion data gets converted to be used w/ a 1-way ANOVA followed by Tukey's HSD. ##### Independent Project: Sample
Example of format for a scientific paper, using data from Whitman, K, AM Starfield, HS Quadling and C Packer. 2004. Sustainable trophy hunting of African lions. Nature. ##### Simple function to plot means w/95% CIs
The is a simple function that plots means as individual points (not bars) & approximate 95% confidence intervals using user-supplied means & standard errors. It provides some feed back via the console & on the plot itself regarding errors and how to make the plot more polished. ##### Lab 9: ANOVA deer antler data
Code needed to generate the different antler datasets for analysis w/ANOVA (mass, basal circumference, main beam, etc) ##### plotTukeysHSD(): plot effect sizes from TukeyHSD object
Takes the output from R's TukeyHSD function for post-hoc comparisons & makes a prettier plot of the output than the default. ##### Paired t-tests: two equivalent ways
A brief walk through of two equivalent ways to conduct a paired t-test, depending on how the data are organized. ##### Lab 5: Intro to t-tests
Intro to t-tests and review of plotting grouped data. Uses Ex 12.4 in Whitlock and Shulter's Analysis of Biological Data, 2nd Ed. ##### Rarefaction notes: iNEXT vs. vegan
General notes on rarefaction for confused pop. ecologists, and comparison of Chao's iNEXT package to vegan. ##### Lab 2a: Displaying Data - boxplot() & hist()
The Iris data Loading data: iris -data(iris) Loading packages in base R: MASS -library(MASS) Loading packages from CRAN: doBy Boxplots w/ iris data -anatomy of an R function -xlab, ylab -cex -lw Histograms w/Iris data -hist Scatterplots w/iris data ##### Lecture 4 ENS 495 Displaying & Describing Data
Displaying & Describing Data. Based on Chapters 2 & 3 in Whitlock & Shulter The Analysis of Biological Data ##### marked R package for mark recapture analysis
In this script I annotate the code for mark-recapture analysis in the R package marked provide in the paper Laake, Johnson and Conn 2013. marked: an R package for maximumlikelihood and Markov ChainMonte Carlo analysis of capture–recapture data. Methods in Ecology and Evolution 4:885–890 and join it with other code produced by the authors in previous publications.