Vertaile menetelmiä

	Yhden sokkoutuksen osittainen faktoriaalikoe	Murtoluku-tekijäkokeen suunnittelu
Tieteenala	Koesuunnittelu	Koesuunnittelu
Menetelmäperhe	Process / pipeline	Process / pipeline
Syntyvuosi	1940s–1950s (fractional factorial foundations); blinding conventions formalised through 1960s–1980s	1945 (Finney); broader development 1950s–1970s by Box, Hunter
Kehittäjä	Fractional factorial theory: R. L. Plackett & J. P. Burman (1946); single-blinding practice codified in clinical trial methodology (20th century)	D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work
Tyyppi	Controlled experimental design	Quantitative experimental design
Alkuperäislähde	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130
Rinnakkaisnimet	single-masked fractional factorial, single-blind FFD, partially blinded fractional factorial, single-blind 2^(k-p) design	fractional factorial design, FFD, 2^(k-p) design, fractional replication
Liittyvät	5	4
Tiivistelmä	A single-blind fractional factorial experiment studies multiple factors simultaneously by testing only a strategically chosen subset — a fraction — of all possible factor-level combinations, while keeping participants unaware of which treatment condition they receive. This design yields substantial information about main effects and selected interactions at a fraction of the cost of a full factorial experiment, with single-blinding reducing participant-side response bias.	A fractional factorial experiment is a resource-efficient experimental design that tests only a carefully chosen fraction of all possible factor-level combinations. By exploiting the principle that high-order interactions are usually negligible, it identifies the main effects and low-order interactions of k factors using far fewer runs than a full factorial design — making it the workhorse of industrial and engineering screening experiments.