Calculating Confidence Interval Estimation Using Maximum Likelihood Estimator For Dataset

Source abstract

Confidence interval estimation is a fundamental technique in statistical inference. Methods for confidence interval estimation used in the literature and implemented in system dynamics software packages typically assume that the data are normally distributed, autocorrelated and homoscedasticity. The objective of this paper is to demonstrate the calculation of confidence interval using maximum likelihood method for fatigue test data for the AISI 8630 M steel for surface roughnes. The advantages of maximum likelihood method are convenience to use and computational efficient. The computational results show that the confidence interval by 90 %, 95% and 99% have significance differences. The width of confidence interval showed that 99% is the highest width compare to 90% and 95%.