Use of a Normality Test to Identify Significant Effects in Factorial Designs

H.C. Benski

49 citations0/0 files storedJournal of Quality Technology

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Optimal Experimental Design Methods Advanced Statistical Methods and Models Advanced Statistical Process Monitoring

Abstract

Graphical techniques are often used to assess the significance of effects in unreplicated factorial experiments. This paper suggests augmenting the graphical procedures by an analytical test of the hypothesis that the calculated effects are a sample from a noncontaminated normal population. This procedure is described and compared to the use of graphical and Bayesian techniques.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 49 citations exist upstream.

References

1979Statistics for Experimenters 1959Use of Half-Normal Plots in Interpreting Factorial Two-Level Experiments 1986An Analysis for Unreplicated Fractional Factorials 1976Applications of Statistics to Industrial Experimentation

Cited by

2004A New Quantitative Method for Analysing Unreplicated Factorial Designs 2001Improving the manufacturing process quality using design of experiments: a case study 1993Finding Significant Effects for Unreplicated Fractional Factorials Using thenSmallest Contrasts

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.