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.
Continue readingSometimes, 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.
Continue readingConverting data type to numeric is important while analyzing the data in R. In this tutorial, we will learn three ways of converting the colums of data frame to numeric. Find out how to convert all columns of data frame to numeric in R.
Continue readingClass of a variable is important while analyzing the data in R. This ultimate tutorial includes three ways of discovering the class of each column in data frame. Find out how to obtain class of each column in R data frame.
Continue readingSorting data may be a necessity while dealing with a data set. In this tutorial, we will learn how to sort a data frame by a single column and multiple columns in an increasing or decreasing order. Find out how to sort a data frame in R.
Continue readingSometimes 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.
Continue readingIdentifying outliers is essential part while analyzing data since they significantly affect a statistical model. This inclusive tutorial covers four tests for detection of outliers. Find out how to test for identifying outliers in R.
Continue readingCorrelation analysis is the important statistical procedure to investigate the relation among the variables. This ultimate guide covers different correlation coefficients and tests for their significance. Find out how to apply correlation analysis in R.
Continue readingOne-way ANOVA is the statistical procedure to test the equality of k independent population means. This comherensive tutorial includes Box-Cox transformation for non-normal and heteroscedastic data to use one-way ANOVA. Find out how to apply one-way ANOVA for non-normal and heteroscedastic data in R.
Continue readingSometimes, there may exist multimodal data while analyzing data. This ultimate tutorial includes detection of multimodal data. Find out how to determine whether data are unimodal or multimodal in R.
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