One-way ANOVA in R

# data loading
dta <- read.csv("file:///C:/Users/bk/Desktop/test2.csv",header = T)
dta

# boxplot data
library(ggplot2)
ggplot(dta, aes(x=group,y=count)) +
  geom_boxplot()

# linear regression model for data
dta.mod1 <- lm(count ~ group,data = dta)

# One-way ANOVA test
res.aov <- aov(count ~ group, dta)
summary(res.aov)

# post-hoc test
TukeyHSD(res.aov)

## TEST Assumptions
# Homogeneity of variance (when p > 0.05, cannot reject null hypothesis: all variances are equal)
bartlett.test(count ~ group,data = dta)

# Normality test (when p > 0.05, cannot reject null hypothesis: data is normally distributed)
aov_residuals <- residuals(object = res.aov)  # extract residuals
shapiro.test(x = aov_residuals)               # run Shapiro-Wilk test