Krahasoni metodat

	Eksperiment faktorial fraksional i dyfishtë i verbër	Eksperiment Frakcional Faktoriel
Fusha	Dizajni eksperimental	Dizajni eksperimental
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1960s onward (combination widely used in pharmaceutical and food science research)	1945 (Finney); broader development 1950s–1970s by Box, Hunter
Krijuesi	Fractional factorial: Box & Hunter (1961); double-blind convention: clinical trial methodology (mid-20th century)	D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work
Lloji	Controlled experimental design with blinding and factor-space reduction	Quantitative experimental design
Burimi themelues	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
Emërtime të tjera	double-blind FFE, blinded fractional factorial design, double-blind FFD, masked fractional factorial experiment	fractional factorial design, FFD, 2^(k-p) design, fractional replication
Të lidhura	3	4
Përmbledhja	A double-blind fractional factorial experiment combines two powerful methodological protections: fractional factorial design, which tests a carefully chosen subset of all possible factor combinations to achieve efficiency, and double-blind administration, which prevents both participants and assessors from knowing which treatment combination has been applied. The result is an experiment that is both resource-efficient and protected against expectation and assessment 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.