Using Permutation Tests in Multiple Correlation Investigation

• Authors: Stelmach, Jacek

Title variants

EN

Wykorzystanie testu permutacyjnego w badaniach korelacji wielowymiarowej

Abstracts

EN

An indication of correlation between dependent variable and predictors is a crucial point in building statistical regression model. The test of Pearson correlation coefficient – with relatively good power – needs to fulfill the assumption about normal distribution. In other cases only non-parametric tests can be used. This article presents a possibility and advantages of permutation tests with the discussion about proposed test statistics. The power of proposed tests was estimated on the basis of Monte Carlo experiments. The investigations were carried out for real data – a sample of refinery process parameters, where the indication of changes in correlation, even for sample with small size is very important. It creates an opportunity to react to changes and update statistical models quickly and keep acceptable quality of prediction

Keywords

EN

permutation tests; Data Mining; correlation analysis; batch process; Monte Carlo

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: Acta Universitatis Lodziensis. Folia Oeconomica
• Year: 2012
• Volume: 269

Dates

published

2012

Contributors

author

Stelmach, Jacek

other

Uniwersytet Ekonomiczny w Katowicach; Wydział Zarządzania; Katedra Statystyki

Identifiers

URI

http://hdl.handle.net/11089/1885