RxP<-read.csv("RxP.csv", stringsAsFactors=T) suppressPackageStartupMessages(library(dplyr)) #Remove the offending data temp<-filter(RxP, Ind!=734 & Ind!=1024 & Ind!=1078 & Ind!=1127 & Ind!=1284) temp<-filter(temp, SVL.initial>12) temp<-filter(temp, Tail.initial<15) #Assign temp to be an object with a useful name RxP.clean<-temp #Remove temp rm(temp) RP.means<-RxP.clean %>% #First, identify the data frame group_by(Res, Pred) %>% #Next, establish grouping variables summarize(SVL.mean = mean(SVL.initial)) #Last, calc. means #Convert the tibble output to a data frame RP.means<-as.data.frame(RP.means) #This is another way to reorder a factor, using dplyr RxP.clean<-RxP.clean %>% mutate(Pred = factor(Pred, levels=c('C','NL','L'))) RP.means<-RxP.clean %>% #Define what dataset we are using group_by(Res, Pred) %>% #Set the groups summarize(SVL.mean = mean(SVL.initial), #Calculate the mean SVL.sd = sd(SVL.initial), #SD SVL.n = length(SVL.initial)) %>% #and N of SVL mutate(SVL.se = SVL.sd/sqrt(SVL.n)) #Calculate the SE before30<-RxP.clean %>% filter(Age.FromEmergence <= 30) after30<-RxP.clean %>% filter(Age.FromEmergence > 30) RxP.clean$before30<-ifelse(RxP.clean$Age.FromEmergence<=30,"Yes","No") #Load the necessary package suppressPackageStartupMessages(library(ggplot2)) suppressPackageStartupMessages(library(cowplot)) suppressPackageStartupMessages(library(gplots)) RP.means2<-RxP.clean %>% #Define what dataset we are using group_by(Hatch, Pred) %>% #Set the groups summarize(Mass.mean = mean(Mass.final), #Calculate the mean, Mass.sd = sd(Mass.final), #Calculate the SD Mass.n = length(Mass.final)) %>% #Calculate the N mutate(Mass.se = Mass.sd/sqrt(Mass.n)) #Calculate the SE RxP.byTank<-RxP.clean %>% group_by(Block,Tank.Unique,Pred,Hatch,Res) %>% summarize(Age.DPO = mean(Age.DPO), Age.FromEmergence = mean(Age.FromEmergence), SVL.initial = mean(SVL.initial), Tail.initial = mean(Tail.initial), SVL.final = mean(SVL.final), Mass.final = mean(Mass.final), Resorb.days = mean(Resorb.days)) RxP.byTank<-as.data.frame(RxP.byTank) suppressPackageStartupMessages(library(MASS)) RxP.byTank$log.SVL.final<-log(RxP.byTank$SVL.final) RxP.byTank$log.Age.FromEmergence<-log(RxP.byTank$Age.FromEmergence) RxP.byTank$log.Age.DPO<-log(RxP.byTank$Age.DPO) lm1<-lm(log.Age.FromEmergence~Pred, data=RxP.byTank) suppressPackageStartupMessages(library(car)) suppressPackageStartupMessages(library(multcomp)) suppressPackageStartupMessages(library(emmeans)) suppressPackageStartupMessages(library(tidyverse)) png('output/rplot.png')

Introduction to R

Thoughts on Proper Data Analysis

Exploratory Data Analysis and Data Summarization

Introduction to Plotting

Basic Statistical Analysis Using R

More Linear Models in R

Advanced Statistical Analysis Using R

Mixed-effects Model

Advanced Data Wrangling and Plotting

Writing Loops and Functions in R

Appendix

Conclusion

Solution: Examine the Effects of Log-transformation on Results

Solution