Cohen's d effect size (for two groups)

Wikipedia: https://en.wikipedia.org/wiki/Effect_size

The effect size is the number of standard deviations falling between the means of the two data sets (mean difference divided by standard deviation [greater?]).
Small - 0.2-0.3
Moderate - 0.5
Large -> 0.8 (can be greater than 1)
The effect size reflects the practical significance of the difference. Note that the statistical significance of the difference ("effect" for independent samples) can be obtained by increasing the sample size even when the differences in the means themselves are minor.

One can use the effsize package to calculate the effect size in R Studio 
(documentation: https://cran.r-project.org/web/packages/effsize/effsize.pdf)

Installation:
install.packages("effsize")
library(effsize)

Sample effect size calculation for two independent samples (paired = FALSE):

length(data_B)
length(data_K)

#Testing normal distribution
shapiro.test(data_B)$p.value
shapiro.test(data_K)$p.value

#Are the average values significantly different?
#if both distributions are normal:
t.test(data_B,data_K,paired = FALSE)
#if at least one distribution is not normal
wilcox.test(data_B,data_K,paired = FALSE)

#Cohen's d effect size
cohen.d(data_B,data_K,paired = FALSE)