Experiment 1 Dommer Bout Analysis

data <- read.csv("Stats.csv")
Day1Treatment <- data[(data$Group.E1Db == 1) & (data$Day.E1Db == 1), ]
Day1NoTreatment <- data[(data$Group.E1Db == 0) & (data$Day.E1Db == 1), ]
Day2Treatment <- data[(data$Group.E1Db == 1) & (data$Day.E1Db == 2), ]
Day2NoTreatment <- data[(data$Group.E1Db == 0) & (data$Day.E1Db == 2), ]
Day3Treatment <- data[(data$Group.E1Db == 1) & (data$Day.E1Db == 3), ]
Day3NoTreatment <- data[(data$Group.E1Db == 0) & (data$Day.E1Db == 3), ]
Day1bTTEST <- t.test(Day1Treatment$Data.E1Db, Day1NoTreatment$Data.E1Db, paired = TRUE)
Day2bTTEST <- t.test(Day2Treatment$Data.E1Db, Day2NoTreatment$Data.E1Db, paired = TRUE)
Day3bTTEST <- t.test(Day3Treatment$Data.E1Db, Day3NoTreatment$Data.E1Db, paired = TRUE)

Day1bTTEST

## 
##  Paired t-test
## 
## data:  Day1Treatment$Data.E1Db and Day1NoTreatment$Data.E1Db
## t = -6.182, df = 7, p-value = 0.0004531
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -69.22 -30.92
## sample estimates:
## mean of the differences 
##                  -50.07

Day2bTTEST

## 
##  Paired t-test
## 
## data:  Day2Treatment$Data.E1Db and Day2NoTreatment$Data.E1Db
## t = -3.947, df = 7, p-value = 0.005556
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -63.57 -15.94
## sample estimates:
## mean of the differences 
##                  -39.75

Day3bTTEST

## 
##  Paired t-test
## 
## data:  Day3Treatment$Data.E1Db and Day3NoTreatment$Data.E1Db
## t = 0.9826, df = 7, p-value = 0.3585
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -15.47  37.46
## sample estimates:
## mean of the differences 
##                      11

data <- read.csv("Stats.csv")
Day1Treatment <- data[(data$Group.E1Dbl == 1) & (data$Day.E1Dbl == 1), ]
Day1NoTreatment <- data[(data$Group.E1Dbl == 0) & (data$Day.E1Dbl == 1), ]
Day2Treatment <- data[(data$Group.E1Dbl == 1) & (data$Day.E1Dbl == 2), ]
Day2NoTreatment <- data[(data$Group.E1Dbl == 0) & (data$Day.E1Dbl == 2), ]
Day3Treatment <- data[(data$Group.E1Dbl == 1) & (data$Day.E1Dbl == 3), ]
Day3NoTreatment <- data[(data$Group.E1Dbl == 0) & (data$Day.E1Dbl == 3), ]
Day1blTTEST <- t.test(Day1Treatment$Data.E1Dbl, Day1NoTreatment$Data.E1Dbl, 
    paired = TRUE)
Day2blTTEST <- t.test(Day2Treatment$Data.E1Dbl, Day2NoTreatment$Data.E1Dbl, 
    paired = TRUE)
Day3blTTEST <- t.test(Day3Treatment$Data.E1Dbl, Day3NoTreatment$Data.E1Dbl, 
    paired = TRUE)

Day1blTTEST

## 
##  Paired t-test
## 
## data:  Day1Treatment$Data.E1Dbl and Day1NoTreatment$Data.E1Dbl
## t = 0.8999, df = 7, p-value = 0.3981
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -14.54  32.40
## sample estimates:
## mean of the differences 
##                   8.931

Day2blTTEST

## 
##  Paired t-test
## 
## data:  Day2Treatment$Data.E1Dbl and Day2NoTreatment$Data.E1Dbl
## t = -1.764, df = 7, p-value = 0.1211
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -66.760   9.713
## sample estimates:
## mean of the differences 
##                  -28.52

Day3blTTEST

## 
##  Paired t-test
## 
## data:  Day3Treatment$Data.E1Dbl and Day3NoTreatment$Data.E1Dbl
## t = -1.579, df = 7, p-value = 0.1583
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -30.221   6.019
## sample estimates:
## mean of the differences 
##                   -12.1