Both t.test ; why different p-values??t.test()&ggboxplot()

[lin]

Code:
p <- ggboxplot(dataA[43:70,], x="time", y="dd", color = "time",palette = "jco", add = "jitter")
p+stat_compare_means(method = "t.test")+ylim(50,60)
t.test(dataA[43:56,1],dataA[57:70,1],paired = FALSE)

p-value should be 0.96,I have no idea why p-value is 0.66 in the boxplot. Both t.test!!
Is there anything wrong??

[Yarnabrina]

Welcome to the community!

I'm unable to reproduce this odd and undesirable behaviour. See below:

library(ggpubr)
#> Loading required package: ggplot2
#> Loading required package: magrittr

ggboxplot(data = ToothGrowth,
          x = "supp",
          y = "len") +
  stat_compare_means(method = "t.test",
                     paired = FALSE,
                     method.args = list(alternative = "greater"))

t.test(formula = (len ~ supp),
       data = ToothGrowth,
       alternative = "greater",
       paired = FALSE)
#> 
#>  Welch Two Sample t-test
#> 
#> data:  len by supp
#> t = 1.9153, df = 55.309, p-value = 0.03032
#> alternative hypothesis: true difference in means is greater than 0
#> 95 percent confidence interval:
#>  0.4682687       Inf
#> sample estimates:
#> mean in group OJ mean in group VC 
#>         20.66333         16.96333

t.test(x = ToothGrowth$len[ToothGrowth$supp == "OJ"],
       y = ToothGrowth$len[ToothGrowth$supp == "VC"],
       alternative = "greater",
       paired = FALSE)
#> 
#>  Welch Two Sample t-test
#> 
#> data:  ToothGrowth$len[ToothGrowth$supp == "OJ"] and ToothGrowth$len[ToothGrowth$supp == "VC"]
#> t = 1.9153, df = 55.309, p-value = 0.03032
#> alternative hypothesis: true difference in means is greater than 0
#> 95 percent confidence interval:
#>  0.4682687       Inf
#> sample estimates:
#> mean of x mean of y 
#>  20.66333  16.96333

^{Created on 2019-03-31 by the reprex package (v0.2.1)}

Can you please provide a REPRoducible EXample of your problem?

In case you don't know how to make a reprex, here's a great link:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…