📢 Our new article published!
"Testing Equality of Shape Parameters of Several Weibull Populations"
🔗 https://t.co/YdM9wzaLDn
👥 Malwane M. A. Ananda, Samaradasa Weerahandi, Osman Dağ
🙏 Thanks to my co-authors for their great efforts!
Our latest article "twowaytests: An R package for two-way tests in independent groups designs" is published on SoftwareX.
🔗https://t.co/OZMkHHrwOY
#DataScience#Statistics#Biostatistics#RStats
3/3✏️You can reach the paper with the following link.
🔗https://t.co/9qY2GaGmIB
🗣 If you are unavailable to reach the paper, you can DM me.
#DataScience#Statistics#Biostatistics#RStats
1/3✍️🏻I am pleased to share that our latest article "Two Approaches to extend Classical MANOVA Tests to the Unequal Covariances Case" is published on Hacettepe Journal of Mathematics and Statistics.
#DataScience#Statistics#Biostatistics#RStats
2/3✍️🏻In this article, we derive two approaches for MANOVA under unequal covariances. I would like to thank to Prof. Sam Weerahandi and Prof. Malwane Ananda for all efforts.
#DataScience#Statistics#Biostatistics#RStats
4 ways of finding unique values in R. It will be very beneficial for the researchers who want to reduce duplicated values in dataset.
#datascience#rstats
Finding unique values may be a necessity while analyzing a data set. In this tutorial, we will learn four ways of finding unique values. Find out how to find unique values in R.
Learn more: https://t.co/S5qU23dXK9
#DataScience#Rstats
How to Use apply Functions in R. Go over apply, tapply, lapply, sapply, vapply and mapply functions in R. It will be very beneficial for the scientists working on data with R.
#datascience#rstats
The use of apply functions enables data scientists to make the things easier. In this tutorial, we go over apply, tapply, lapply, sapply, vapply and mapply. Find out how to use apply functions in R.
Learn more: https://t.co/SvkTYwhqJT
#DataScience#Rstats
Sometimes, we need to merge datasets coming from different sources. This ultimate tutorial includes combining the data frames in different ways. Find out how to merge data frames in R.
Learn more: https://t.co/G8cYhKa3vb
#DataScience#Rstats
Converting data type to numeric is important while analyzing data in R. We will learn three ways of converting the columns of data frame to numeric. Find out how to convert all columns of data frame to numeric in R.
Learn more: https://t.co/vhVigg2H0A
#DataScience#Rstats
Very nice start to New Year!
Our latest paper "GeneSelectML: a comprehensive way of gene selection for RNA-Seq data via machine learning algorithms" is published on Medical & Biological Engineering & Computing.
https://t.co/FDCKAPecPG
#datascience#machinelearning#rstats
Class of a variable is important while analyzing data in R. This ultimate tutorial includes three ways of discovering class of each column in data frame. Find out how to obtain class of each column in R data frame.
Learn more: https://t.co/Anwv1j3sBh
#DataScience#Rstats
How to sort a data frame by a single column and multiple columns in increasing or decreasing order!
Learn more: https://t.co/wjormEVWuz
#DataScience#Rstats
I'm pleased to share that our latest article "Ensemble Based Box-Cox Transformation via Meta Analysis" is published on Journal of Advanced Research in Natural and Applied Sciences.
https://t.co/2WkvPTRUEL
#datascience#rstats#statistics#biostatistics
I am happy to share that our latest article "Diverse Classifiers Ensemble Based on GMDH-Type Neural Network Algorithm for Binary Classification" is published on Communications in Statistics - Simulation&Computation.
https://t.co/82LeEqFdkg
#datascience#machinelearning#rstats
I am very happy to share that our article "Heteroscedastic two-way ANOVA under constraints" is published on Communications in Statistics - Theory and Methods. You can reach the tests through twowaytests package in R.
https://t.co/qPoljTvRZJ
#DataScience#RStats
Sometimes we need to remove outliers from data. In this tutorial, we learn how to remove outliers from data including multi-variables, a single variable and data by group in R. Find out how to remove outliers from data in R.
https://t.co/NYsctuCbXG
#datascience#rstats
Identifying outliers is essential part while analyzing data since they significantly affect statistical models. This inclusive tutorial covers four tests for detecting outliers. Find out how to test for identifying outliers in R.
https://t.co/fcmpcbNWo7
#datascience#rstats
I have recognized a package called “correlation”. It is very comprehensive package for correlation analysis.
I have written a short note for myself and shared to whom are interested in.
https://t.co/nn8H7Q80rZ
#datascience#rstats
Two sample independent tests are the mostly used methods in studies. This comherensive guide includes the tests for two independent samples when the outcome is continuous. Find out how to use these tests in R.
https://t.co/SckqpCfHLu
#datascience#rstats