Introduction: Whenever we mention the word statistics or statistical procedures, the mean, standard deviation, Pearson correlation coefficient and normal curve are the concepts that come to mind. The Gaussian probability distribution (affectionately known as normal) and its companion least-squares estimators are the foundations for classical statistical procedures and measurement theory. ... Unfortunately the limitations and assumptions are often ignored without regard to what the resulting statistics may or may not represent if our data are not truly Gaussian
Let (X, Y) be bivariate normally distributed with means (μ 1, μ 2), variances (σ 1 2, σ 2 2 ) and co...
Nonparametric correlation measures at the Kendall and Spearman correlation are widely used in the be...
The Gaussian rank correlation equals the usual correlation coefficient computed from the normal scor...
A Monte Carlo investigation of six robust correlation estimators was conducted for data from distrib...
The study of the association between two random variables that have a joint normal distribution is o...
The word correlation in general indicates that two quantities are related and somehow linked togethe...
Classical correlation coefficient is a powerful statistical analysis when measuring a relationship b...
A monte carlo experiment was conducted to evaluate the robustness of two estimators of the populati...
The objective of this research was to propose a composite correlation coefficient to estimate the ra...
Monte-Carlo simulation is used to compare the small-sample performance of the usual normal theory pr...
Two statistics are considered to test the population correlation for non-normally distributed bivari...
Many inferential statistical tests require that the observed variables have a normal distribution. M...
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147087/1/rssc01350.pd
The Gaussian rank correlation equals the usual correlation coefficient computed from the normal scor...
This paper derives the asymptotic analytical forms of the mean and variance of the Gini correlation ...
Let (X, Y) be bivariate normally distributed with means (μ 1, μ 2), variances (σ 1 2, σ 2 2 ) and co...
Nonparametric correlation measures at the Kendall and Spearman correlation are widely used in the be...
The Gaussian rank correlation equals the usual correlation coefficient computed from the normal scor...
A Monte Carlo investigation of six robust correlation estimators was conducted for data from distrib...
The study of the association between two random variables that have a joint normal distribution is o...
The word correlation in general indicates that two quantities are related and somehow linked togethe...
Classical correlation coefficient is a powerful statistical analysis when measuring a relationship b...
A monte carlo experiment was conducted to evaluate the robustness of two estimators of the populati...
The objective of this research was to propose a composite correlation coefficient to estimate the ra...
Monte-Carlo simulation is used to compare the small-sample performance of the usual normal theory pr...
Two statistics are considered to test the population correlation for non-normally distributed bivari...
Many inferential statistical tests require that the observed variables have a normal distribution. M...
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147087/1/rssc01350.pd
The Gaussian rank correlation equals the usual correlation coefficient computed from the normal scor...
This paper derives the asymptotic analytical forms of the mean and variance of the Gini correlation ...
Let (X, Y) be bivariate normally distributed with means (μ 1, μ 2), variances (σ 1 2, σ 2 2 ) and co...
Nonparametric correlation measures at the Kendall and Spearman correlation are widely used in the be...
The Gaussian rank correlation equals the usual correlation coefficient computed from the normal scor...