DisgustBayes

Import the Data

## Loading required package: coda
## Loading required package: lattice
## ************
## Welcome to BayesFactor 0.9.10-2. If you have questions, please contact Richard Morey (richarddmorey@gmail.com).
## 
## Type BFManual() to open the manual.
## ************
## Loading required package: survival
## Loading required package: splines
## The following `from` values were not present in `x`: +4 You very strongly agree with the statement.

Lets do the redo the tests and show the Bayes Factor

---

Gender difference in Before Cricket rating

# Standard test
x1 <- dat$BeforeCricket[dat$Sex=="Female"]
y1 <- dat$BeforeCricket[dat$Sex=="Male"]
wilcox.test(x1, y1, alternative = "t")

## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  x1 and y1
## W = 10602.5, p-value = 3.978e-06
## alternative hypothesis: true location shift is not equal to 0

##Bayesian t-test: via Bayes factor
ttestBF(x = dat$BeforeCricket[dat$Sex=="Female"],
        y = dat$BeforeCricket[dat$Sex=="Male"], paired=FALSE)

## Bayes factor analysis
## --------------
## [1] Alt., r=0.707 : 4828.835 ±0%
## 
## Against denominator:
##   Null, mu1-mu2 = 0 
## ---
## Bayes factor type: BFindepSample, JZS

JZS BF₁₀ = 4828.84 Decisive evidence

---

Gender difference in Before Bar rating

# Before Cricket Bar Gender Difference
x2 <- dat$BeforeCricketBar[dat$Sex=="Female"]
y2 <- dat$BeforeCricketBar[dat$Sex=="Male"]
wilcox.test(x2, y2, alternative = "t")

## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  x2 and y2
## W = 11688.5, p-value = 0.000534
## alternative hypothesis: true location shift is not equal to 0

##Bayesian t-test: via Bayes factor
ttestBF(x = dat$BeforeCricketBar[dat$Sex=="Female"],
        y = dat$BeforeCricketBar[dat$Sex=="Male"], paired=FALSE)

## Bayes factor analysis
## --------------
## [1] Alt., r=0.707 : 181.7985 ±0%
## 
## Against denominator:
##   Null, mu1-mu2 = 0 
## ---
## Bayes factor type: BFindepSample, JZS

JZS BF₁₀ = 181.8 Decisive evidence

---

Influence difference in Cricket change rating

# Whitney-Mann U (also known as two-sample Wilcoxon)
x1 <- dat$CricketChange[dat$Group=="Group A"]
y1 <- dat$CricketChange[dat$Group=="Group B"]
wilcox.test(x1, y1, alternative = "t", paired=FALSE)

## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  x1 and y1
## W = 15873.5, p-value = 0.3167
## alternative hypothesis: true location shift is not equal to 0

##Bayesian t-test: via Bayes factor
ttestBF(x = dat$CricketChange[dat$Group=="Group A"],
        y = dat$CricketChange[dat$Group=="Group B"], paired=FALSE)

## Bayes factor analysis
## --------------
## [1] Alt., r=0.707 : 0.1331407 ±0%
## 
## Against denominator:
##   Null, mu1-mu2 = 0 
## ---
## Bayes factor type: BFindepSample, JZS

JZS BF₁₀ = 0.13 Substantial evidence in favor of the null

---

Influence difference in Bar change rating

# Whitney-Mann U (also known as two-sample Wilcoxon)
x2 <- dat$BarChange[dat$Group=="Group A"]
y2 <- dat$BarChange[dat$Group=="Group B"]
wilcox.test(x2, y2, alternative = "t", paired=FALSE)

## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  x2 and y2
## W = 13409, p-value = 0.02839
## alternative hypothesis: true location shift is not equal to 0

##Bayesian t-test: via Bayes factor
ttestBF(x = dat$BarChange[dat$Group=="Group A"],
        y = dat$BarChange[dat$Group=="Group B"], paired=FALSE)

## Bayes factor analysis
## --------------
## [1] Alt., r=0.707 : 3.920118 ±0%
## 
## Against denominator:
##   Null, mu1-mu2 = 0 
## ---
## Bayes factor type: BFindepSample, JZS

JZS BF₁₀ = 3.92 Substantial evidence