More technical volcano for golub data.

Valine in red color and aspartic acid in black color.

It a plot for statistical distribution of the age of patients with melanoma.

It's a circlize plot for iris, between its Species and clustered Sepal_Length.

scatterplot3d::scatterplot3d(xp, yp, zp, type = 'l', lwd = 3)

illustrating random selection in normal data.

just a beautiful plot.

R features for making beautiful density plots.

R features for making some beautiful density plot

features of R for making beautiful density plots.

P-value adjustment is useful in some experimental methods like the analysis of microarray. reference: https://stat.ethz.ch/R-manual/R-devel/library/stats/html/p.adjust.html

Principal component analysis of Wisconsin Breast cancer data. It's interesting that data variables are located in 1/3 part of the circle.

unregressed data! what is it look like?

Correlation between columns of iris data. It's interesting that between some of them there is a CC bigger than 0.9.

One question about two-way ANOVA is, what is the face of data with a significant effect of two factors? Or we can say, in what form of data a two-way ANOVA will give us a p.value less than 0.05 for the interaction effects of two factors?

Prediction to fit the curve estimated by mgcv::gam. Mohammad Taghizadeh

means<-numeric(10000) for (i in 1:10000){ means[i]<-mean(runif(5)*10) } hist(means,ylim=c(0,1600)) xa <- seq(0,10,0.1) ya <- dnorm(xa,mean=4.998581,sd=1.28996)*5000 lines(xa,ya) box()

My honor to R and RStudio.

Best dimension peak for 2D clustering of iris dataset.

Volcano Plot for golub data from multtest R package: this dataset is for the microarray of ALL and AML leukemias. Mohammad Taghizadeh, PhD in bioinformatics.