Σύγκριση μεθόδων

	Σχεδίαση Πλήρως Τυχαιοποιημένη (CRD)	Πειραματικός Σχεδιασμός Πλήρους Παραγοντικού Τύπου	Μονόδρομη Ανάλυση Διακύμανσης
Πεδίο	Πειραματικός Σχεδιασμός	Πειραματικός Σχεδιασμός	Στατιστική
Οικογένεια	Hypothesis test	Hypothesis test	Hypothesis test
Έτος προέλευσης	1935	1926	1925
Δημιουργός	R. A. Fisher	R. A. Fisher	Ronald A. Fisher
Τύπος	Parametric group comparison via one-way ANOVA	Parametric factorial experiment	Parametric mean comparison
Θεμελιώδης πηγή	Montgomery, D.C. (2017). Design and Analysis of Experiments. Wiley. ISBN: 978-1119320937	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
Εναλλακτικές ονομασίες	CRD, completely randomised design, one-way experimental design, Tam Tesadüf Deneme Deseni (CRD)	factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Συναφείς	3	5	4
Σύνοψη	The completely randomized design is the most fundamental experimental design, in which experimental units are assigned to treatments entirely at random with no restrictions. Analysed by one-way ANOVA, it was formalised by R. A. Fisher in the 1930s and remains the reference starting point for experimental research whenever the experimental material is homogeneous and nuisance variation is absent or negligible.	A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured.	One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.