Data transformations are commonly used tools that can serve many functions in quantitative analysis of data. The goal of this paper is to focus on the use of three data transformations most commonly discussed in statistics texts (square root, log, and inverse) for improving the normality of variables. While these are important options for analysts, they do fundamentally transform the nature of the variable, making the interpretation of the results somewhat more complex. Further, few (if any) statistical texts discuss the tremendous influence a distribution\u27s minimum value has on the efficacy of a transformation. The goal of this paper is to promote thoughtful and informed use of data transformations. Accessed 244,249 times on https://par...
The main purpose of this dissertation is to study the transformations on difference cases of data. T...
Templeton and Burney (2017) proposed a two-step normality transformation as a remedy for non-normall...
It is not uncommon to have situations where highly skewed data appear in research investigations. In...
Data transformations are commonly used tools that can serve many functions in quantitative..analysis...
Data transformations are commonly used tools in quantitative analysis of data. However, data transfo...
Introduction Data transformations such as replacing a variable by its logarithm or by its square-roo...
Data transformations have been promoted as a popular and easy-to-implement remedy to address the ass...
Applications of statistical techniques are common in scientific and multidisciplinary research. Stat...
Many of us in the social sciences deal with data that do not conform to assumptions of normality and...
The problem of normalization of data is frequently discussed in the literature but few studies have ...
The problem of normalization of data is frequently discussed in the literature but few studies have ...
<div><p>ABSTRACT. There are researchers who do not recommend data transformation arguing it causes p...
When testing the difference between two groups, if previous data indicate non-normality, then either...
Background: Logarithmic transformation is recommended in method comparison or commutability studies ...
Introduction: Sometimes the mapping of the variable values made during the measurement needs to be t...
The main purpose of this dissertation is to study the transformations on difference cases of data. T...
Templeton and Burney (2017) proposed a two-step normality transformation as a remedy for non-normall...
It is not uncommon to have situations where highly skewed data appear in research investigations. In...
Data transformations are commonly used tools that can serve many functions in quantitative..analysis...
Data transformations are commonly used tools in quantitative analysis of data. However, data transfo...
Introduction Data transformations such as replacing a variable by its logarithm or by its square-roo...
Data transformations have been promoted as a popular and easy-to-implement remedy to address the ass...
Applications of statistical techniques are common in scientific and multidisciplinary research. Stat...
Many of us in the social sciences deal with data that do not conform to assumptions of normality and...
The problem of normalization of data is frequently discussed in the literature but few studies have ...
The problem of normalization of data is frequently discussed in the literature but few studies have ...
<div><p>ABSTRACT. There are researchers who do not recommend data transformation arguing it causes p...
When testing the difference between two groups, if previous data indicate non-normality, then either...
Background: Logarithmic transformation is recommended in method comparison or commutability studies ...
Introduction: Sometimes the mapping of the variable values made during the measurement needs to be t...
The main purpose of this dissertation is to study the transformations on difference cases of data. T...
Templeton and Burney (2017) proposed a two-step normality transformation as a remedy for non-normall...
It is not uncommon to have situations where highly skewed data appear in research investigations. In...