@article{IPI1408078,
title = "ESTIMASI DATA HILANG PADA RANCANGAN ACAK KELOMPOK LENGKAP",
journal = "MATEMATIKA",
volume = "Vol 10, No 2 (2007): JURNAL MATEMATIKA",
pages = "",
year = "2007",
url = https://ejournal.undip.ac.id/index.php/matematika/article/view/869/739
author = "widiharih, Tatik",
abstract = "Randomized complete block design is a design to reduce the residual error in an experiment by removing variability due to a known and controllable nuisance variable. Missing observations introduce a new problem into the analysis since treatments are no longer orthogonal to blocks, that is, every treatment does not occur in every block, There are two general approaches to the missing values problem. The first is an exact analysis, the second is an approaximate analysis in which the missing observations are estimated and usual analysis of variance is performed just as if the estimated observations were real data, with the error degrees of freedom reduced by the number of missing observations. In this paper was discussed the second approach with completely analysis. Biggerâ€™s method is a simple method for estimating missing observations by using matrix approximation. Â ",
}