Elementary proof of the independence of mean and variance of samples from a normal distribution. Usually the independence of mean and variance of samples from a normal distribution is proven by some n-dimensional reasoning. The present article starts by proving the independence of the sample-mean mn and the "deviation" xn–mn–1 of the last sampled element from the previous sample-mean. This result gives an easy approach to the independence theorem, which is proven by a step-by-step process. A more elaborate version of the proof reveals the nature of the s-distribution. Use is made of the n–i deviations xi–mi-1(i = 2, 3, …, n), which are completely independent and represent the n–1 degrees of freedom in s
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
We use the independence of the integer and fractional parts of exponentially distributed random vari...
There are several tests for testing independence of two variables, but a shortage of tests that can ...
Elementary proof of the independence of mean and variance of samples from a normal distribution. Usu...
Abstract. Of a11 the characterizations of Ule normal distribution, three landmarks are the theorems ...
International audienceIn this paper, we present three remarkable properties of the normal distributi...
The problem of determining a statistical population belonging to a certain class of distributions is...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
For some cases it may be permissible to assume that the correlation between each two normal random v...
Texte intégral sur le site: https://www.scienpress.comIn this paper, we present three remarkable pro...
This paper gives results for the population value of a measure of the goodness-of-fit of a general m...
The normal law is characterised through the local independence of certain statistics
This paper gives results for the population value of a measure of the goodness-of-fit of a general m...
International audienceThis paper proposes a semi-parametric test of independence (or serial independ...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
We use the independence of the integer and fractional parts of exponentially distributed random vari...
There are several tests for testing independence of two variables, but a shortage of tests that can ...
Elementary proof of the independence of mean and variance of samples from a normal distribution. Usu...
Abstract. Of a11 the characterizations of Ule normal distribution, three landmarks are the theorems ...
International audienceIn this paper, we present three remarkable properties of the normal distributi...
The problem of determining a statistical population belonging to a certain class of distributions is...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
For some cases it may be permissible to assume that the correlation between each two normal random v...
Texte intégral sur le site: https://www.scienpress.comIn this paper, we present three remarkable pro...
This paper gives results for the population value of a measure of the goodness-of-fit of a general m...
The normal law is characterised through the local independence of certain statistics
This paper gives results for the population value of a measure of the goodness-of-fit of a general m...
International audienceThis paper proposes a semi-parametric test of independence (or serial independ...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
We use the independence of the integer and fractional parts of exponentially distributed random vari...
There are several tests for testing independence of two variables, but a shortage of tests that can ...