--- title: "Lab 05 - Data Summary" author: "WILD 502 - Jay Rotella" output: pdf_document --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` ## Bring in the Data ```{r, message = FALSE} library(tidyverse) library(GGally) library(RMark) sq <- convert.inp("http://www.montana.edu/rotella/documents/502/SwampSquirrels.inp", group.df = data.frame(age = c("juv","older")), covariates = c("birth", "tail")) head(sq, 4) # select just the covariates that will be used in modeling sq.covs <- sq %>% select(birth, tail, age) head(sq.covs, 4) ``` ## Some useful Summary Statistics Here, we have 2 continuous covariates and 1 categorical. ```{r, message = FALSE} summary(sq.covs) # get SDs for continuous covariates apply(sq.covs[, 1:2], 2, sd) ggpairs(sq.covs, aes(color = age, alpha = 0.2)) ``` ```{r, message = FALSE, fig.width=3, fig.height=3} ggplot(sq.covs, aes(x = age, y = birth)) + geom_boxplot() + geom_point(pch = 21, position = position_jitter()) ggplot(sq.covs, aes(x = age, y = tail)) + geom_boxplot() + geom_point(pch = 21, position = position_jitter()) ```