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ROO PLOTS TO DETECT POSSIBLE OUTLIERS IN UNREPLICATED 2k COMPLETELY RANDOMIZED FACTORIAL DESIGNS: NUMERICAL EXAMPLE
| Content Provider | Semantic Scholar |
|---|---|
| Author | Fitrianto, Anwar |
| Copyright Year | 2015 |
| Abstract | Two-level unreplicated factorial design is very common in manufacturing industries. The design can be used to save cost since it usually needs less experimental run. But, problems appears when the experiment is done with any replication. When there is no replication in such kind of experiment, we will face problem in identifying significant terms as well as to identify possible outlier in the data. This article discusses about the use of Pareto plot to identify significant terms for unreplicated two-level factorial experiments through numerical example. Meanwhile, we also use the same example to clearly describe how to create and interpret both ROO and iteractive ROO plot in identifying possible outlier in the experimental data. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0916_4984.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
