The main purpose of this work is to describe three well-known statistical tests of independence in two-by-two contingency tables. We will deeply study chi- squared test of independence, Fisher's exact test and Barnard's test and apply them on examples. Also we will describe, in general, categorical variables, which are often analysed using a multinomial distribution. At the end we will apply tests on the examples, using data simulated from a multinomial and binomial distribution.
A new approach is described for improving statistical tests of independence between two categorical ...
AbstractConsider an r × c contingency table under the full multinomial model where each category is ...
New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually ...
The main purpose of this work is to describe three well-known statistical tests of independence in t...
This report is a survey of the literature for a combination of different tests for both two-way and ...
This report is a survey of the literature for a combination of different tests for both two-way and ...
Testing for the independence between two categorical variables R and S forming a contingency table i...
AbstractTesting for the independence between two categorical variables R and S forming a contingency...
Testing for the independence between two categorical variables R and S forming a contingency table i...
Several test statistics are available for testing the independence of categorical variables from two...
A new approach is described for improving statistical tests of independence between two categorical ...
A new approach is described for improving statistical tests of independence between two categorical ...
This thesis deals with the problem of independence testing between two discrete ran- dom variables. ...
nonparametric regression; conditional independence; adjusted Nadaraya-Watson estimator; long-range d...
AbstractTesting for the independence between two categorical variables R and S forming a contingency...
A new approach is described for improving statistical tests of independence between two categorical ...
AbstractConsider an r × c contingency table under the full multinomial model where each category is ...
New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually ...
The main purpose of this work is to describe three well-known statistical tests of independence in t...
This report is a survey of the literature for a combination of different tests for both two-way and ...
This report is a survey of the literature for a combination of different tests for both two-way and ...
Testing for the independence between two categorical variables R and S forming a contingency table i...
AbstractTesting for the independence between two categorical variables R and S forming a contingency...
Testing for the independence between two categorical variables R and S forming a contingency table i...
Several test statistics are available for testing the independence of categorical variables from two...
A new approach is described for improving statistical tests of independence between two categorical ...
A new approach is described for improving statistical tests of independence between two categorical ...
This thesis deals with the problem of independence testing between two discrete ran- dom variables. ...
nonparametric regression; conditional independence; adjusted Nadaraya-Watson estimator; long-range d...
AbstractTesting for the independence between two categorical variables R and S forming a contingency...
A new approach is described for improving statistical tests of independence between two categorical ...
AbstractConsider an r × c contingency table under the full multinomial model where each category is ...
New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually ...