Experiment 1 Falafel Bout Analysis

data <- read.csv("Stats.csv")
Day1Treatment <- data[(data$Group.E1Fb == 1) & (data$Day.E1Fb == 1), ]
Day1NoTreatment <- data[(data$Group.E1Fb == 0) & (data$Day.E1Fb == 1), ]
Day2Treatment <- data[(data$Group.E1Fb == 1) & (data$Day.E1Fb == 2), ]
Day2NoTreatment <- data[(data$Group.E1Fb == 0) & (data$Day.E1Fb == 2), ]
Day3Treatment <- data[(data$Group.E1Fb == 1) & (data$Day.E1Fb == 3), ]
Day3NoTreatment <- data[(data$Group.E1Fb == 0) & (data$Day.E1Fb == 3), ]
Day1bTTEST <- t.test(Day1Treatment$Data.E1Fb, Day1NoTreatment$Data.E1Fb, paired = TRUE)
Day2bTTEST <- t.test(Day2Treatment$Data.E1Fb, Day2NoTreatment$Data.E1Fb, paired = TRUE)
Day3bTTEST <- t.test(Day3Treatment$Data.E1Fb, Day3NoTreatment$Data.E1Fb, paired = TRUE)

Day1bTTEST

## 
##  Paired t-test
## 
## data:  Day1Treatment$Data.E1Fb and Day1NoTreatment$Data.E1Fb
## t = -5.38, df = 8, p-value = 0.000662
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -55.11 -22.04
## sample estimates:
## mean of the differences 
##                  -38.58

Day2bTTEST

## 
##  Paired t-test
## 
## data:  Day2Treatment$Data.E1Fb and Day2NoTreatment$Data.E1Fb
## t = -5.369, df = 8, p-value = 0.0006706
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -44.87 -17.91
## sample estimates:
## mean of the differences 
##                  -31.39

Day3bTTEST

## 
##  Paired t-test
## 
## data:  Day3Treatment$Data.E1Fb and Day3NoTreatment$Data.E1Fb
## t = 1.992, df = 8, p-value = 0.08149
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.716 37.202
## sample estimates:
## mean of the differences 
##                   17.24

data <- read.csv("Stats.csv")
Day1Treatment <- data[(data$Group.E1Fbl == 1) & (data$Day.E1Fbl == 1), ]
Day1NoTreatment <- data[(data$Group.E1Fbl == 0) & (data$Day.E1Fbl == 1), ]
Day2Treatment <- data[(data$Group.E1Fbl == 1) & (data$Day.E1Fbl == 2), ]
Day2NoTreatment <- data[(data$Group.E1Fbl == 0) & (data$Day.E1Fbl == 2), ]
Day3Treatment <- data[(data$Group.E1Fbl == 1) & (data$Day.E1Fbl == 3), ]
Day3NoTreatment <- data[(data$Group.E1Fbl == 0) & (data$Day.E1Fbl == 3), ]
Day1blTTEST <- t.test(Day1Treatment$Data.E1Fbl, Day1NoTreatment$Data.E1Fbl, 
    paired = TRUE)
Day2blTTEST <- t.test(Day2Treatment$Data.E1Fbl, Day2NoTreatment$Data.E1Fbl, 
    paired = TRUE)
Day3blTTEST <- t.test(Day3Treatment$Data.E1Fbl, Day3NoTreatment$Data.E1Fbl, 
    paired = TRUE)

Day1blTTEST

## 
##  Paired t-test
## 
## data:  Day1Treatment$Data.E1Fbl and Day1NoTreatment$Data.E1Fbl
## t = -5.685, df = 8, p-value = 0.0004622
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -58.66 -24.80
## sample estimates:
## mean of the differences 
##                  -41.73

Day2blTTEST

## 
##  Paired t-test
## 
## data:  Day2Treatment$Data.E1Fbl and Day2NoTreatment$Data.E1Fbl
## t = -5.107, df = 8, p-value = 0.0009214
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -49.88 -18.85
## sample estimates:
## mean of the differences 
##                  -34.36

Day3blTTEST

## 
##  Paired t-test
## 
## data:  Day3Treatment$Data.E1Fbl and Day3NoTreatment$Data.E1Fbl
## t = 2.996, df = 8, p-value = 0.01718
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   7.614 58.523
## sample estimates:
## mean of the differences 
##                   33.07