Confidence Intervals for the Population Correlation Coefficient
DOI:
https://doi.org/10.6000/1929-6029.2016.05.02.4Keywords:
Bivariate distribution, Bootstrapping, Correlation coefficient, Confidence interval, Simulation studyAbstract
Computing a confidence interval for a population correlation coefficient is very important for researchers as it gives an estimated range of values which is likely to include an unknown population correlation coefficient. This paper studied some confidence intervals for estimating the population correlation coefficient ρ by means of a Monte Carlo simulation study. Data are randomly generated from several bivariate distributions with a various values of sample sizes. Assessment measures such as coverage probability, mean width and standard deviation of the width are selected for performances evaluation. Two real life data are analyzed to demonstrate the application of the proposed confidence intervals. Based on our findings, some good confidence intervals for a population correlation coefficient are suggested for practitioners and applied researchers.
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Copyright (c) 2016 Shipra Banik, B.M. Golam Kibria
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