Repository for SNR's R User Group https://chrischizinski.github.io/SNR_R_Group/ Next up we were utilizing multivariate methods to assess the statistical difference among groups. Here are the class notebooks covering this material: R notebook-Discriminant function analysis Fri, 01 Dec 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-12-01-GroupDifferences https://chrischizinski.github.io/SNR_R_Group//2017-12-01-GroupDifferences We spent some time covering the latent variable analysis this semester. Here are the class notebooks covering this material R notebook-Factor Analysis part 1 R notebook-Factor Analysis part 2 R notebook-Latent Class Analysis Fri, 13 Oct 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-10-13-LatentVariables https://chrischizinski.github.io/SNR_R_Group//2017-10-13-LatentVariables We continue to cover identifying groups in multivariate data. This class will focus on cluster analysis. This is a broad topic and could probably cover most of a semester, if you want more in depth start by looking at: Notebook files R notebook-Cluster part 2 R notebook Rmarkdown file-Cluster part... Fri, 06 Oct 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-10-06-Cluster2 https://chrischizinski.github.io/SNR_R_Group//2017-10-06-Cluster2 This class covers an introduction to dissimilarity and distance measures. Detailed notes from previous semesters can be found here: 2016-08-12-SimilarityDistance. R notebook R notebook Rmarkdown file Weekly challenge Take home challenges No challenge this week Fri, 29 Sep 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-09-29-Dissimilarites https://chrischizinski.github.io/SNR_R_Group//2017-09-29-Dissimilarites This topic will span a couple classes and include topics such as cluster analysis, factor analysis, and latent class analysis R notebook-Cluster part 1 R notebook Rmarkdown file-Cluster part 1 Fri, 29 Sep 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-09-29-Cluster1 https://chrischizinski.github.io/SNR_R_Group//2017-09-29-Cluster1 This class continues to cover an introduction to multivariate statistics and data transformations and standardizations. Detailed notes from previous semesters can be found here: 2016-08-10-Data-Transformations. R notebook R notebook Rmarkdown file Weekly challenge Take home challenges No challenge this week Fri, 22 Sep 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-09-22-Datastandardizations https://chrischizinski.github.io/SNR_R_Group//2017-09-22-Datastandardizations This class covers an introduction to multivariate statistics and data transformations and standardizations. Detailed notes from previous semesters can be found here: 2016-08-10-Data-Transformations. Introduction presentation Introduction presentation Rmarkdown file R notebook R notebook Rmarkdown file Weekly challenge Take home challenges Input the file from "https://ndownloader.figshare.com/files/2292169" Use data from Rodents only... Fri, 15 Sep 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-09-15-Introtomultivariate https://chrischizinski.github.io/SNR_R_Group//2017-09-15-Introtomultivariate This class covers an introduction to graphing using the functions from ggplot2. Similar to the introduction with tidyverse This is only meant to serve as a brief introduction and we will keep developing these skills throughout the semester. I have similar lessons graphing from a previous semester 2016-10-03-BasicPlots and information... Fri, 08 Sep 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-09-08-Introtoggplot2 https://chrischizinski.github.io/SNR_R_Group//2017-09-08-Introtoggplot2 This class covers an introduction to wrangling and summarizing data using the functions from tidyr and dplyr. This is only meant to serve as a brief introduction, as we will keep developing these skills throughout the semester. I have a similar lesson on data wrangling from a previous semester 2016-09-23-Wrangling... Fri, 01 Sep 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-09-01-IntrotoDataWrangling https://chrischizinski.github.io/SNR_R_Group//2017-09-01-IntrotoDataWrangling Welcome back to another semester of our UseR. R script from class Powerpoint from class Weekly challenge The data Work with the ecology data set from datacarpentry. An explanation of the dataset can be found here library(tidyverse)mydata <- read_csv("https://ndownloader.figshare.com/files/2292169")glimpse(mydata) ## Observations: 34,786## Variables: 13## $ record_id <int> 1, 72, 224,... Fri, 25 Aug 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-08-25-IntrotoR https://chrischizinski.github.io/SNR_R_Group//2017-08-25-IntrotoR library(tidyverse)library(broom) Sources of the notes for this lecture are from Ecological Detective (Chapter 5). Simplest technique for the confrontation between models and data is sum of squares It is simple and makes few assumptions Long and successful history in science Computers can do remarkable calcualations associated with sum of squares... Fri, 14 Apr 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-04-14-SumofSquares https://chrischizinski.github.io/SNR_R_Group//2017-04-14-SumofSquares library(tidyverse)library(broom) Sources of the notes for this lecture are from Ecological Detective (Chapter 4). Motivation Non-target species are often caught during fishing operations Observer programs are used to monitor this incidental catch Understanding of the coverage of the program and how to interpret the data is needed hauls = c(807,... Thu, 30 Mar 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-03-30-IncidentalCatch https://chrischizinski.github.io/SNR_R_Group//2017-03-30-IncidentalCatch library(tidyverse)library(broom) Sources of the notes for this lecture are a combination of Aho(2013) (Chapters 2 and 3) and Ecological Detective (Chapters 3 and 4). Common distributions Discrete Negative binomial distribution Negative binomial gives the probability that x independent Bernoulli failures will occur prior to obtaining the rth success - two... Fri, 17 Mar 2017 00:00:00 -0500 https://chrischizinski.github.io/SNR_R_Group//2017-03-17-EcologicalDetective6 https://chrischizinski.github.io/SNR_R_Group//2017-03-17-EcologicalDetective6 library(tidyverse) Classical Probability Sources of the notes for this lecture are a combination of Aho(2013) (Chapters 2 and 3) and Ecological Detective (Chapters 3 and 4). As we become familiar with the behavior of random variables, we may become aware of probabilistic patterns Disjoint If two events can not occur... Fri, 10 Mar 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-03-10-EcologicalDetective5 https://chrischizinski.github.io/SNR_R_Group//2017-03-10-EcologicalDetective5 What about for a six sided die? Let’s take the coin-flipping example from last week and run a similar test on a six sided dice. Lets run a simulation from 1 to 5000 dice rolls and calculated the proportion of each number. For example, a 1 will be a single... Fri, 03 Mar 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-03-03-SixSidedDieRolls https://chrischizinski.github.io/SNR_R_Group//2017-03-03-SixSidedDieRolls Exploring the relationship between two variables First lets bring in the data from the previous lesson library(tidyverse)library(broom) fish_data <- read_csv("https://raw.githubusercontent.com/chrischizinski/MWFWC_FishR/master/CourseMaterial/data/wrkshp_data.csv") ## Parsed with column specification:## cols(## .default = col_character(),## WaterbodyCode = col_integer(),## Area = col_integer(),## MethodCode = col_integer(),## surveydate = col_datetime(format = ""),## Station = col_integer(),## Effort = col_integer(),## SpeciesCode... Thu, 23 Feb 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-02-23-EcologicalDetective3 https://chrischizinski.github.io/SNR_R_Group//2017-02-23-EcologicalDetective3 Recreating Figure 2.1 in Ecological Detective There are many different hypotheses that can explain the basic relationship between two variables. Figure 2.1 in the Ecologial Detective suggest 4 possible models. The models have no parameter values. Try to iteratively find the parameter values to get your figure to look like... Fri, 10 Feb 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-02-10-EcologicalDetective2 https://chrischizinski.github.io/SNR_R_Group//2017-02-10-EcologicalDetective2 Ecological Detective Preface: Beyond the Null hypothesis Tools of an Ecological Detective Classic Hypothesis Testing M~1~: Boom and bust (complete extinction between colonizations) hypothesis M~2~: Constant prevalance of population but only is detected when certain conditions arise H~0~: Model M1 is true H~A~: Some other model is true Outcome: M~2~... Fri, 03 Feb 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-02-03-EcologicalDetective1 https://chrischizinski.github.io/SNR_R_Group//2017-02-03-EcologicalDetective1 This is just a gentle introduction to what you can do with Rmarkdown. There are lots of tutorials out there to help you further (Software carpentry, Data carpentry). There is also a lot more you can do with it than I have shown here. For example, you can alter the... Fri, 20 Jan 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-01-20-Rmarkdowntutorial https://chrischizinski.github.io/SNR_R_Group//2017-01-20-Rmarkdowntutorial Getting to know R again (with some new stuff thrown in) Using data from Google sheets (kind of) Google Forms is a quick and cheap way to put together an online survey. I asked you all to do the survey through Google Forms so that we can run some of... Fri, 13 Jan 2017 00:00:00 -0600 https://chrischizinski.github.io/SNR_R_Group//2017-01-13-GettingtoKnowRAgain https://chrischizinski.github.io/SNR_R_Group//2017-01-13-GettingtoKnowRAgain