Rounding is importaint to increase the resolution for meaningful analysis and data interpretation. This inclusive tutorial includes six ways of rounding data frame in which character variables exist. Find out how to round data frame containing character variables in R.
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GMDH-type neural network algorithm is a heuristic self-organizing algorithm to model complex systems. This ultimate guide involves feature selection and classification via GMDH algorithm for a binary response. Find out how to apply GMDH algorithm in R.
Continue readingTwo 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.
Continue readingLoops are the most powerful tools of the R programming language. This comprehensive guide includes the types of loops in R – for, while, repeat. Find out how to use loops in R.
Continue readingVariance homogeneity is one of the most certain assumptions for parametric hypothesis tests. This inclusive guide covers the tests of variance homogeneity. Find out how to check variance homogeneity in R.
Continue readingNormality has an essential role since the most of the statistical methods are based on normal distribution. This ultimate guide includes the ways of checking normality. Find out how to assess normality in R.
Continue readingShapiro-Wilk test is one of the most well-known tests for assessing the normality of data. This comprehensive guide includes the ways of applying Shapiro-Wilk test for univariate and multivariate normality. Find out how to use Shapiro-Wilk test in R.
Continue readingCategorizing numeric variables is very common task in data processing. This inclusive guide covers the ways of categorizing numerical data. Find out how to convert numerical data to categories in R.
Continue readingRecoding character variables is the important part in data manuplation. This comprehensive guide covers all steps of recoding a character variable. Find out how to revalue character data in R.
Continue readingHandling missing values is the crucial process before data analysis. This ultimate guide covers all important aspects of handling missing (NA) values. Find out how to deal with NA values in R.
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