Experiment 1 Falafel Wheel and Motion

data <- read.csv("Stats.csv")
Day1Treatment <- data[(data$Group.E1FWheel == 1) & (data$Day.E1FWheel == 1), 
    ]
Day1NoTreatment <- data[(data$Group.E1FWheel == 0) & (data$Day.E1FWheel == 1), 
    ]
Day2Treatment <- data[(data$Group.E1FWheel == 1) & (data$Day.E1FWheel == 2), 
    ]
Day2NoTreatment <- data[(data$Group.E1FWheel == 0) & (data$Day.E1FWheel == 2), 
    ]
Day3Treatment <- data[(data$Group.E1FWheel == 1) & (data$Day.E1FWheel == 3), 
    ]
Day3NoTreatment <- data[(data$Group.E1FWheel == 0) & (data$Day.E1FWheel == 3), 
    ]
Day1WTTEST <- t.test(Day1Treatment$Data.E1FWheel, Day1NoTreatment$Data.E1FWheel, 
    paired = TRUE)
Day2WTTEST <- t.test(Day2Treatment$Data.E1FWheel, Day2NoTreatment$Data.E1FWheel, 
    paired = TRUE)
Day3WTTEST <- t.test(Day3Treatment$Data.E1FWheel, Day3NoTreatment$Data.E1FWheel, 
    paired = TRUE)

Day1WTTEST

## 
##  Paired t-test
## 
## data:  Day1Treatment$Data.E1FWheel and Day1NoTreatment$Data.E1FWheel
## t = -5.77, df = 9, p-value = 0.0002695
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -55.47 -24.22
## sample estimates:
## mean of the differences 
##                  -39.85

Day2WTTEST

## 
##  Paired t-test
## 
## data:  Day2Treatment$Data.E1FWheel and Day2NoTreatment$Data.E1FWheel
## t = -3.673, df = 9, p-value = 0.00513
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -47.93 -11.39
## sample estimates:
## mean of the differences 
##                  -29.66

Day3WTTEST

## 
##  Paired t-test
## 
## data:  Day3Treatment$Data.E1FWheel and Day3NoTreatment$Data.E1FWheel
## t = 3.15, df = 9, p-value = 0.01174
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   9.801 59.740
## sample estimates:
## mean of the differences 
##                   34.77

data <- read.csv("Stats.csv")
Day1Treatment <- data[(data$Group.E1FMotion == 1) & (data$Day.E1FMotion == 1), 
    ]
Day1NoTreatment <- data[(data$Group.E1FMotion == 0) & (data$Day.E1FMotion == 
    1), ]
Day2Treatment <- data[(data$Group.E1FMotion == 1) & (data$Day.E1FMotion == 2), 
    ]
Day2NoTreatment <- data[(data$Group.E1FMotion == 0) & (data$Day.E1FMotion == 
    2), ]
Day3Treatment <- data[(data$Group.E1FMotion == 1) & (data$Day.E1FMotion == 3), 
    ]
Day3NoTreatment <- data[(data$Group.E1FMotion == 0) & (data$Day.E1FMotion == 
    3), ]
Day1MTTEST <- t.test(Day1Treatment$Data.E1FMotion, Day1NoTreatment$Data.E1FMotion, 
    paired = TRUE)
Day2MTTEST <- t.test(Day2Treatment$Data.E1FMotion, Day2NoTreatment$Data.E1FMotion, 
    paired = TRUE)
Day3MTTEST <- t.test(Day3Treatment$Data.E1FMotion, Day3NoTreatment$Data.E1FMotion, 
    paired = TRUE)

Day1MTTEST

## 
##  Paired t-test
## 
## data:  Day1Treatment$Data.E1FMotion and Day1NoTreatment$Data.E1FMotion
## t = -4.398, df = 9, p-value = 0.001726
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -61.25 -19.64
## sample estimates:
## mean of the differences 
##                  -40.45

Day2MTTEST

## 
##  Paired t-test
## 
## data:  Day2Treatment$Data.E1FMotion and Day2NoTreatment$Data.E1FMotion
## t = -1.786, df = 9, p-value = 0.1077
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -45.146   5.307
## sample estimates:
## mean of the differences 
##                  -19.92

Day3MTTEST

## 
##  Paired t-test
## 
## data:  Day3Treatment$Data.E1FMotion and Day3NoTreatment$Data.E1FMotion
## t = 1.609, df = 9, p-value = 0.142
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -10.96  65.01
## sample estimates:
## mean of the differences 
##                   27.02