Package install

Packages <- c("tidyverse", "car", "dunn.test","onewaytests","FSA")
lapply(Packages, library, character.only = TRUE)

Data import

d1<- read.csv("/Users/koho0/Desktop/1st 2 group stats/Fig 2_2hr interval_female Gephyrin_1day.csv")

Data structure

str(d1)
## 'data.frame':    10 obs. of  3 variables:
##  $ subject   : int  1 2 3 4 5 6 7 8 9 10
##  $ group     : Factor w/ 2 levels "con","sevo": 1 1 1 1 1 2 2 2 2 2
##  $ F_gephyrin: num  0.623 0.671 0.763 0.92 0.734 ...

Explorative data analysis with graphics

Easystat function developed by S. Park (available at https://rpubs.com/goodlebang)

Statistical Result

easystat(d1)
## 1. Normality assumption test by Shapiro_Wilk test is 
##  p = 0.26 
##  Normality assumption was not rejected 
## 2. Equal variance test by Bartlett test is 
##  p = 0.609 
##  Equal variance assumption was not rejected 
## 3. The result of anova is 
##  p = 0.035 
##  A statistically significant difference exist between groups
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = d1[, 3] ~ d1[, 2], data = d1)
## 
## $`d1[, 2]`
##               diff        lwr       upr     p adj
## sevo-con 0.2118255 0.01846153 0.4051894 0.0354663