Correlation coefficients are generally viewed as summaries, causing them to be underutilized. Creating functions from them leads to their use in diverse areas of statistics. Because there are many correlation coefficients (see, for example, Gideon (2007)) this extension makes possible a very broad range of statistical estimators that rivals least squares. The whole area could be called a Correlation Estimation System. This paper outlines some of the numerous possibilities for using the system and gives some illustrative examples. Detailed explanations are developed in earlier papers. The formulae to make possible both the estimation and some of the computer coding to implement it are given. This approach has been taken in hopes that this ...
In this article, a nonparametric correlation coefficient is defined that is based on the principle o...
In the correlation model, the classical coefficient of multiple determination 2 is a measure of asso...
This short note takes correlation coefficients as the starting point to obtain inferential results i...
A generalized method of defining and interpreting correlation coefficients is given. Seven correlati...
This presentation contains a new system of estimation, starting with correlation coefficients, that ...
This paper, third in a series on the correlation estimation system (CES), shows how to use any corre...
This article takes correlation coefficients as the starting point to obtain inferential results in l...
A measure of correlation or strength of association between random variables is the correlation coef...
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
The aim of this thesis is to give a proper description of the correlation coeffient and its usage. T...
The Pearson correlation coefficient (r) is usually the first measure of association taught...
The purpose of this paper is to introduce researchers to correlation coefficient calculation. The Pe...
This short piece provides an introduction to the use of Kendall's t in correlation and simple l...
Many people who do data analysis take only a few classes in statistics and hence, in general, get in...
AbstractPearson (1905) introduced the correlation ratio η2 as a measure for the non-linear influence...
In this article, a nonparametric correlation coefficient is defined that is based on the principle o...
In the correlation model, the classical coefficient of multiple determination 2 is a measure of asso...
This short note takes correlation coefficients as the starting point to obtain inferential results i...
A generalized method of defining and interpreting correlation coefficients is given. Seven correlati...
This presentation contains a new system of estimation, starting with correlation coefficients, that ...
This paper, third in a series on the correlation estimation system (CES), shows how to use any corre...
This article takes correlation coefficients as the starting point to obtain inferential results in l...
A measure of correlation or strength of association between random variables is the correlation coef...
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
The aim of this thesis is to give a proper description of the correlation coeffient and its usage. T...
The Pearson correlation coefficient (r) is usually the first measure of association taught...
The purpose of this paper is to introduce researchers to correlation coefficient calculation. The Pe...
This short piece provides an introduction to the use of Kendall's t in correlation and simple l...
Many people who do data analysis take only a few classes in statistics and hence, in general, get in...
AbstractPearson (1905) introduced the correlation ratio η2 as a measure for the non-linear influence...
In this article, a nonparametric correlation coefficient is defined that is based on the principle o...
In the correlation model, the classical coefficient of multiple determination 2 is a measure of asso...
This short note takes correlation coefficients as the starting point to obtain inferential results i...