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Планування експерименту 実験計画法 Statistische Versuchsplanung Projektowanie eksperymentów Plan d'expériences Diseño experimental Plánování experimentů Design of experiments Планирование эксперимента تصميم التجارب 试验设计 Statistische onderzoeksplanning Perancangan percobaan Försöksplanering Diseinu esperimental Disseny d'experiments 실험계획법
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Diseinu esperimentala ikerketa esperimental baten barruan eragin baten kausak identifikatu eta kuantifikatzeko aukera ematen duen teknika estatistiko bat da. Diseinu esperimental batean, aldagai bat edo gehiago, kausekin lotuta, nahita manipulatzen dira interesgarri den beste aldagai batean duten eragina neurtzeko. Aurrez zehaztutako konfiantza-mailarekin ustezko kausa-ondorio erlazio baten beharra ezartzeko, diseinu esperimentalak jarraibide batzuk agintzen ditu zein aldagai manipulatu behar diren, zein modutan, zenbat aldiz errepikatu behar den esperimentua eta zer ordenatan. El disseny d'experiments o disseny experimental, en anglès: Design of experiments (DOE) o experimental design és el disseny de qualsevol exercici de recollida d'informació on es presenta variació, sigui sota el control total de l'experiment o no. Tanmateix en estadística, aquests termes normalment es fan servir per . Vegeu experiment per la distinció entre els tipus d'experiments o estudis. Die statistische Versuchsplanung, kurz SVP (englisch design of experiments, DoE), umfasst alle statistischen Verfahren, die vor Versuchsbeginn angewendet werden sollten. Dazu gehören: * die Bestimmung des minimal erforderlichen Versuchsumfanges zur Einhaltung von Genauigkeitsvorgaben, siehe Trennschärfe eines Tests * die Anordnung von Versuchspunkten innerhalb des Faktorraums anhand eines Optimalitätskriteriums (I-, D-, A-, G-optimale Versuchspläne) * Methoden zum Umgang mit Störgrößen wie Blöcke, Randomisierung, lateinische Quadrate * , vor allem fraktionierte faktorielle Pläne * und Auswertung (Sequentialanalyse); hier wechseln Datenerfassung und -auswertung ab, bis eine vorgegebene Genauigkeit erreicht wird Планирование эксперимента (англ. experimental design techniques) — это процедура выбора числа опытов и условий их проведения, необходимых для решения поставленной задачи с требуемой точностью. Основная цель планирования эксперимента — достижение максимальной точности измерений при минимальном количестве проведенных опытов и сохранении статистической достоверности результатов. Планирование эксперимента применяется при поиске оптимальных условий, построении интерполяционных формул, выборе значимых факторов, оценке и уточнении констант теоретических моделей и др. On nomme plan d'expériences (en anglais, design of experiments ou DOE) la suite ordonnée d'essais d'une expérimentation, chacun permettant d'acquérir de nouvelles connaissances en maîtrisant un ou plusieurs paramètres d'entrée pour obtenir des résultats validant un modèle avec une bonne économie de moyens (nombre d'essais le plus faible possible, par exemple). 實驗設計(英文:design of experiments ,DOE),又称試驗設計或设计试验,是数理统计学的一个分支,科學探究的一部份,涉及「用何方法可更好的設計一個實驗」,屬於方法論的範疇。由於任何實驗都會受到外來環境影響,如何設計實驗,使外來環境的變化能夠對實驗造成最小的影響,就是實驗規劃的目的。實驗設計法廣泛用於自然科學、社會科學、医学等各學科的實驗設計裡。 The design of experiments (DOE, DOX, or experimental design) is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation. Statistische onderzoeksplanning (Engels: design of experiments, DoE) wordt bij het ontwikkelen en optimaliseren van producten en processen gebruikt. Omdat het doen van experimenten tijd, materiaal en productiecapaciteit in beslag neemt staat men voor een dilemma: voor een betrouwbaar onderzoeksresultaat is een groot aantal experimenten noodzakelijk maar tegelijkertijd mag het beslag op resources niet groter zijn dan strikt noodzakelijk. Door gebruik te maken van statistische onderzoeksplanning wordt met een zo klein mogelijk aantal experimenten met zo veel mogelijk betrouwbaarheid het verband tussen onafhankelijke variabelen ("knoppen" waar aan gedraaid kan worden) en afhankelijke variabelen (procesuitkomsten) bepaald. El diseño experimental es una técnica estadística que permite identificar y cuantificar las causas de un efecto dentro de un estudio experimental. En un diseño experimental se manipulan deliberadamente una o más variables, vinculadas a las causas, para medir el efecto que tienen en otra variable de interés. El diseño experimental prescribe una serie de pautas relativas qué variables hay que manipular, de qué manera, cuántas veces hay que repetir el experimento y en qué orden para poder establecer con un grado de confianza predefinido la necesidad de una presunta relación de causa-efecto. Plánování experimentů, návrh experimentů či experimentální design je disciplína matematické statistiky, která se zabývá sběrem dat v situaci, kdy je získávaná informace zatížena nahodilostí. Součástí experimentu obvykle je intervence (zásah) experimentátora (například metoda ošetření pacienta), přičemž cílem je zjistit efekt této intervence. Dobře navržený experiment umožňuje usuzovat na kauzální působení intervencí. Základy moderní teorie plánování experimentů vyložil Ronald A. Fisher v knize The Design of Experiments (1935). Hlavní myšlenky návrhu experimentů jsou: 실험계획법(實驗計劃法, design of experiments, DOE)은 효율적인 실험 방법을 설계하고 결과를 제대로 분석하는 것을 목적으로하는 통계학의 응용 분야이다. 로널드 피셔가 1920년대에 농업 실험에서 영감을 얻어 발전시켰다. 이후 의학, 공학, 실험 심리학과 사회학에 널리 적용되었다. 또한 마케팅 등에서 콘조인트 분석도 사용된다. 実験計画法(じっけんけいかくほう、英: Experimental design、Design of experiments)は、効率のよい実験方法を設計(デザイン)し、結果を適切に解析することを目的とする統計学の応用分野である。R・A・フィッシャーが1920年代に農学試験から着想して発展させた。特に1950年G・M・コックスとW・G・コクランが標準的教科書を出版し、以後医学、工学、実験心理学や社会調査へ広く応用された。またこれを基にして田口玄一による品質工学という新たな分野も生まれた。 他にも、マーケティングや新しい商品・サービスのコンセプトや仕様を考える場合などに用いられる、コンジョイント分析も有用である。 تصميم التجارب (بالإنجليزية: (DOE, DOX) experimental design) هو تصميم أي مهمة تهدف إلى وصف وشرح تباين المعلومات في ظل ظروف يُفترض أنها تعكس التباين. يرتبط المصطلح عمومًا بالتجارب التي يقدم فيها التصميم ظروفًا تؤثر بشكل مباشر على التباين، ولكن قد يشير أيضًا إلى تصميم شبه التجارب، حيث يتم اختيار الظروف الطبيعية التي تؤثر على التباين للمراقبة. تعمل التجارب المصممة بشكل صحيح على تعزيز المعرفة في العلوم الطبيعية والاجتماعية والهندسة. تشمل التطبيقات الأخرى التسويق وصنع السياسات. تعد دراسة تصميم التجارب موضوعًا مهمًا في . Планува́ння експериме́нту (рос. планирование эксперимента, англ. experimental design, design of experiments, нім. Versuchsplanung f, Testplanung f) — процедура вибору числа та умов проведення дослідів, необхідних та достатніх для вирішення задачі досліджень із заданою точністю. Projektowanie eksperymentów (planowanie doświadczeń, teoria eksperymentu; ang. design of experiments, w skrócie DOE) – interdyscyplinarna dziedzina nauki znajdująca się na pograniczu statystyki, metrologii, matematyki stosowanej oraz informatyki, mająca na celu dostarczenie odpowiedzi na pytanie o możliwość takiego zaplanowania doświadczenia (eksperymentu lub quasi-eksperymentu), aby uzyskać możliwie najwięcej użytecznych informacji przy najmniejszych koniecznych do tego kosztach. Perancangan percobaan atau rancangan percobaan (Design of Experiment) adalah kajian mengenai penentuan kerangka dasar kegiatan pengumpulan informasi terhadap objek yang memiliki variasi (stokastik), berdasarkan prinsip-prinsip statistika. Bidang ini merupakan salah satu cabang penting dalam statistika inferensial dan diajarkan di banyak cabang ilmu pengetahuan di perguruan tinggi karena berkaitan erat dengan pelaksanaan percobaan (eksperimen). Försöksplanering är statistiska metoder för att ta fram linjära samband och samverkanseffekter mellan faktorer i processer. Syftet är att med ett rimligt antal försök ta fram hur en process kan justeras för att optimera utfallet. Det kan röra sig om produktionsprocesser, exempelvis gjutmaskiner, eller andra processer, exempelvis reningsanläggningar. Ofta innebär detta att man varierar flera faktorer på samma gång enligt ett beräknat mönster, och sedan använder en statistisk programvara för att analysera resultatet för att se vilka faktorer som påverkar utfallet, och hur dessa bör justeras för att optimera processens utfall.
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Diseinu esperimentala ikerketa esperimental baten barruan eragin baten kausak identifikatu eta kuantifikatzeko aukera ematen duen teknika estatistiko bat da. Diseinu esperimental batean, aldagai bat edo gehiago, kausekin lotuta, nahita manipulatzen dira interesgarri den beste aldagai batean duten eragina neurtzeko. Aurrez zehaztutako konfiantza-mailarekin ustezko kausa-ondorio erlazio baten beharra ezartzeko, diseinu esperimentalak jarraibide batzuk agintzen ditu zein aldagai manipulatu behar diren, zein modutan, zenbat aldiz errepikatu behar den esperimentua eta zer ordenatan. Diseinu esperimentalak industrian, nekazaritzan, marketinean, medikuntzan, ekologian, portaera zientzietan eta abarretan aplikazioak aurkitzen ditu, azterketa esperimental baten garapenean ezinbesteko fasea osatuz. Perancangan percobaan atau rancangan percobaan (Design of Experiment) adalah kajian mengenai penentuan kerangka dasar kegiatan pengumpulan informasi terhadap objek yang memiliki variasi (stokastik), berdasarkan prinsip-prinsip statistika. Bidang ini merupakan salah satu cabang penting dalam statistika inferensial dan diajarkan di banyak cabang ilmu pengetahuan di perguruan tinggi karena berkaitan erat dengan pelaksanaan percobaan (eksperimen). Perancangan percobaan dapat dikatakan sebagai "jembatan" bagi peneliti untuk bergerak dari hipotesis menuju pada eksperimen agar memberikan hasil yang valid secara ilmiah. Dengan demikian, perancangan percobaan dapat dikatakan sebagai salah satu instrumen dalam metode ilmiah. Kajian perancangan percobaan adalah pelaksanaan percobaan (eksperimen) terkendali. Dalam percobaan semacam ini, peneliti memberikan sejumlah tindakan (dapat juga "pelabelan" sesuai dengan ciri-ciri objeknya, diistilahkan sebagai atau treatment) pada sejumlah objek yang memiliki variasi pada derajat tertentu. Objek ini diistilahkan sebagai atau experimental unit, yang dapat berwujud hewan, tumbuhan, manusia, atau barang. Apabila perlakuan yang sama dikenakan terhadap sejumlah objek, objek-objek ini merupakan (replicate) dari perlakuan tadi. dilakukan terhadap sejumlah karakteristik yang diminati sang peneliti terhadap objek-objek tadi. Hipotesis statistis ditentukan ("") untuk memaknai pengaruh perlakuan-perlakuan yang diberikan terhadap hasil pengamatan (data) yang ada. Beberapa pustaka menggunakan istilah experimental design bagi untuk rancangan-rancangan yang dibuat untuk kegiatan pengumpulan informasi tidak terkendali, seperti survei, jajak pendapat (polling), (natural experiment), dan . Meskipun hal ini memiliki dasar statistika, kajian klasik perancangan percobaan tidak mencakup tipe-tipe penelitian semacam itu. El diseño experimental es una técnica estadística que permite identificar y cuantificar las causas de un efecto dentro de un estudio experimental. En un diseño experimental se manipulan deliberadamente una o más variables, vinculadas a las causas, para medir el efecto que tienen en otra variable de interés. El diseño experimental prescribe una serie de pautas relativas qué variables hay que manipular, de qué manera, cuántas veces hay que repetir el experimento y en qué orden para poder establecer con un grado de confianza predefinido la necesidad de una presunta relación de causa-efecto. El diseño experimental encuentra aplicaciones en la industria, la agricultura, la mercadotecnia, la medicina, la ecología, las ciencias de la conducta, etc. constituyendo una fase esencial en el desarrollo de un estudio experimental. 実験計画法(じっけんけいかくほう、英: Experimental design、Design of experiments)は、効率のよい実験方法を設計(デザイン)し、結果を適切に解析することを目的とする統計学の応用分野である。R・A・フィッシャーが1920年代に農学試験から着想して発展させた。特に1950年G・M・コックスとW・G・コクランが標準的教科書を出版し、以後医学、工学、実験心理学や社会調査へ広く応用された。またこれを基にして田口玄一による品質工学という新たな分野も生まれた。 他にも、マーケティングや新しい商品・サービスのコンセプトや仕様を考える場合などに用いられる、コンジョイント分析も有用である。 實驗設計(英文:design of experiments ,DOE),又称試驗設計或设计试验,是数理统计学的一个分支,科學探究的一部份,涉及「用何方法可更好的設計一個實驗」,屬於方法論的範疇。由於任何實驗都會受到外來環境影響,如何設計實驗,使外來環境的變化能夠對實驗造成最小的影響,就是實驗規劃的目的。實驗設計法廣泛用於自然科學、社會科學、医学等各學科的實驗設計裡。 تصميم التجارب (بالإنجليزية: (DOE, DOX) experimental design) هو تصميم أي مهمة تهدف إلى وصف وشرح تباين المعلومات في ظل ظروف يُفترض أنها تعكس التباين. يرتبط المصطلح عمومًا بالتجارب التي يقدم فيها التصميم ظروفًا تؤثر بشكل مباشر على التباين، ولكن قد يشير أيضًا إلى تصميم شبه التجارب، حيث يتم اختيار الظروف الطبيعية التي تؤثر على التباين للمراقبة. تصميم التجارب يتبع في عمليات التطوير والتحسين للمنتجات أو العمليات الإنتاجية. التجارب بحاجة إلى مصادر (أشخاص، زمن، أجهزة... الخ) ولهذا يكون المسؤول عنها ما بين حالتين متنافرتين نسبياً، فهو من ناحية يسعى إلى دقة النتائج من العمل ومن ناحية أخرى يجب أن يراعي الوقت والجهد الممكنين.تصميم التجارب الإحصائية يقوم على الاعتماد على أقل عدد ممكن من التجارب لتحديد العلاقة بين عوامل التأثير (كل ما يؤثر على عملية إنتاج أو تصنيع) والنتائج المطلوبة. في أبسط أشكالها، تهدف التجربة إلى التنبؤ بالنتيجة من خلال إدخال تغيير في الشروط المسبقة، والذي يتم تمثيله بواسطة واحد أو أكثر من المتغيرات المستقلة، والتي يشار إليها أيضًا باسم «متغيرات الإدخال» أو «متغيرات التنبؤ». يُفترض عمومًا أن يؤدي التغيير في واحد أو أكثر من المتغيرات المستقلة إلى تغيير واحد أو أكثر من المتغيرات التابعة، والتي يشار إليها أيضًا باسم «متغيرات الإخراج» أو «متغيرات الاستجابة». قد يحدد التصميم التجريبي أيضًا التي يجب أن تظل ثابتة لمنع العوامل الخارجية من التأثير على النتائج. لا يقتصر التصميم التجريبي على اختيار المتغيرات المستقلة والمعتمدة والمتغيرات الضابطة فحسب، بل يشمل أيضًا التخطيط لتسليم التجربة في ظل الظروف المثلى إحصائيًا نظرًا لقيود الموارد المتاحة. هناك طرق متعددة لتحديد مجموعة نقاط التصميم (مجموعات فريدة من إعدادات المتغيرات المستقلة) لاستخدامها في التجربة. تشمل الاهتمامات الرئيسية في التصميم التجريبي إنشاء والموثوقية وإمكانية التكرار. على سبيل المثال، يمكن معالجة هذه المخاوف جزئيًا عن طريق اختيار المتغير المستقل بعناية، وتقليل مخاطر خطأ القياس، والتأكد من أن توثيق الطريقة مفصل بشكل كافٍ. تشمل الاهتمامات ذات الصلة تحقيق مستويات مناسبة من والحساسية. تعمل التجارب المصممة بشكل صحيح على تعزيز المعرفة في العلوم الطبيعية والاجتماعية والهندسة. تشمل التطبيقات الأخرى التسويق وصنع السياسات. تعد دراسة تصميم التجارب موضوعًا مهمًا في . El disseny d'experiments o disseny experimental, en anglès: Design of experiments (DOE) o experimental design és el disseny de qualsevol exercici de recollida d'informació on es presenta variació, sigui sota el control total de l'experiment o no. Tanmateix en estadística, aquests termes normalment es fan servir per . Vegeu experiment per la distinció entre els tipus d'experiments o estudis. En el disseny d'experiments, l'experiment sovint està interessat en l'efecte d'alguns processos o intervencions (el "tractament") sobre alguns objectes (les ""), les quals poden ser les persones, parts de les persones, grups de persones, plantes, animals, materials, etc. El disseny d'experiments és una disciplina que té moltes aplicacions en les ciències naturals i socials. Планирование эксперимента (англ. experimental design techniques) — это процедура выбора числа опытов и условий их проведения, необходимых для решения поставленной задачи с требуемой точностью. Основная цель планирования эксперимента — достижение максимальной точности измерений при минимальном количестве проведенных опытов и сохранении статистической достоверности результатов. Планирование эксперимента применяется при поиске оптимальных условий, построении интерполяционных формул, выборе значимых факторов, оценке и уточнении констант теоретических моделей и др. The design of experiments (DOE, DOX, or experimental design) is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation. In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as "input variables" or "predictor variables." The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables." The experimental design may also identify control variables that must be held constant to prevent external factors from affecting the results. Experimental design involves not only the selection of suitable independent, dependent, and control variables, but planning the delivery of the experiment under statistically optimal conditions given the constraints of available resources. There are multiple approaches for determining the set of design points (unique combinations of the settings of the independent variables) to be used in the experiment. Main concerns in experimental design include the establishment of validity, reliability, and replicability. For example, these concerns can be partially addressed by carefully choosing the independent variable, reducing the risk of measurement error, and ensuring that the documentation of the method is sufficiently detailed. Related concerns include achieving appropriate levels of statistical power and sensitivity. Correctly designed experiments advance knowledge in the natural and social sciences and engineering. Other applications include marketing and policy making. The study of the design of experiments is an important topic in metascience. Die statistische Versuchsplanung, kurz SVP (englisch design of experiments, DoE), umfasst alle statistischen Verfahren, die vor Versuchsbeginn angewendet werden sollten. Dazu gehören: * die Bestimmung des minimal erforderlichen Versuchsumfanges zur Einhaltung von Genauigkeitsvorgaben, siehe Trennschärfe eines Tests * die Anordnung von Versuchspunkten innerhalb des Faktorraums anhand eines Optimalitätskriteriums (I-, D-, A-, G-optimale Versuchspläne) * Methoden zum Umgang mit Störgrößen wie Blöcke, Randomisierung, lateinische Quadrate * , vor allem fraktionierte faktorielle Pläne * und Auswertung (Sequentialanalyse); hier wechseln Datenerfassung und -auswertung ab, bis eine vorgegebene Genauigkeit erreicht wird Da Versuche Ressourcen benötigen (Personal, Zeit, Geräte usw.), sieht sich der Versuchsverantwortliche in einem Zwiespalt zwischen einerseits der Genauigkeit und Zuverlässigkeit seiner erwarteten Ergebnisse und andererseits dem dazu notwendigen Aufwand. Der Begriff „Versuch“ schließt neben materiellen Versuchen die Rechnersimulationen mit ein.Mit der statistischen Versuchsplanung wird mit möglichst wenigen Versuchen (Einzelexperimenten) der Wirkzusammenhang zwischen Einflussfaktoren (= unabhängige Variablen) und Zielgrößen (= abhängige Variable) möglichst genau ermittelt. Wichtiger Bestandteil der statistischen Versuchsplanung ist die Bestimmung des Versuchsumfanges in Abhängigkeit von Genauigkeitsvorgaben wie etwa der Risiken von statistischen Tests und der minimal interessierenden Mindestdifferenz vom Nullhypothesenwert. Projektowanie eksperymentów (planowanie doświadczeń, teoria eksperymentu; ang. design of experiments, w skrócie DOE) – interdyscyplinarna dziedzina nauki znajdująca się na pograniczu statystyki, metrologii, matematyki stosowanej oraz informatyki, mająca na celu dostarczenie odpowiedzi na pytanie o możliwość takiego zaplanowania doświadczenia (eksperymentu lub quasi-eksperymentu), aby uzyskać możliwie najwięcej użytecznych informacji przy najmniejszych koniecznych do tego kosztach. Rozwój teorii eksperymentu związany był z założoną przez Johna Benneta Lawesa słynną rolniczą Stację Eksperymentalną Rothamsted w Harpenden. W czasie kiedy jej dyrektorem był Edward John Russell, w stacji zatrudniony został Ronald Fisher (autor pracy The design of experiments z 1935 r.), a więc kluczowa postać dla rozwoju zarówno statystyki, jak i dziedziny projektowania eksperymentów. Od tego czasu stacja stała się instytucją w której pracowali badacze mający znaczny wpływ na rozwój planowania doświadczeń: Frank Yates, Joseph Oscar Irwin, John Wishart, William Gemmell Cochran (współautor, wspólnie Gertrude Mary Cox, książki pt. Experimental Designs z 1950 r.) i John Nelder. Statistische onderzoeksplanning (Engels: design of experiments, DoE) wordt bij het ontwikkelen en optimaliseren van producten en processen gebruikt. Omdat het doen van experimenten tijd, materiaal en productiecapaciteit in beslag neemt staat men voor een dilemma: voor een betrouwbaar onderzoeksresultaat is een groot aantal experimenten noodzakelijk maar tegelijkertijd mag het beslag op resources niet groter zijn dan strikt noodzakelijk. Door gebruik te maken van statistische onderzoeksplanning wordt met een zo klein mogelijk aantal experimenten met zo veel mogelijk betrouwbaarheid het verband tussen onafhankelijke variabelen ("knoppen" waar aan gedraaid kan worden) en afhankelijke variabelen (procesuitkomsten) bepaald. Планува́ння експериме́нту (рос. планирование эксперимента, англ. experimental design, design of experiments, нім. Versuchsplanung f, Testplanung f) — процедура вибору числа та умов проведення дослідів, необхідних та достатніх для вирішення задачі досліджень із заданою точністю. Försöksplanering är statistiska metoder för att ta fram linjära samband och samverkanseffekter mellan faktorer i processer. Syftet är att med ett rimligt antal försök ta fram hur en process kan justeras för att optimera utfallet. Det kan röra sig om produktionsprocesser, exempelvis gjutmaskiner, eller andra processer, exempelvis reningsanläggningar. Ofta innebär detta att man varierar flera faktorer på samma gång enligt ett beräknat mönster, och sedan använder en statistisk programvara för att analysera resultatet för att se vilka faktorer som påverkar utfallet, och hur dessa bör justeras för att optimera processens utfall. Plánování experimentů, návrh experimentů či experimentální design je disciplína matematické statistiky, která se zabývá sběrem dat v situaci, kdy je získávaná informace zatížena nahodilostí. Součástí experimentu obvykle je intervence (zásah) experimentátora (například metoda ošetření pacienta), přičemž cílem je zjistit efekt této intervence. Dobře navržený experiment umožňuje usuzovat na kauzální působení intervencí. Základy moderní teorie plánování experimentů vyložil Ronald A. Fisher v knize The Design of Experiments (1935). Hlavní myšlenky návrhu experimentů jsou: * Srovnání – pro posouzení efektu intervence je třeba porovnat objekty vystavené této intervenci a objekty, které jí vystaveny nebyly (tzv. ). * Randomizace (znáhodnění) – výběr jednotek, které budou pozorovány, vystaveny různým druhům intervence resp. budou zařazeny do kontrolní skupiny, se musí dít na základě pravděpodobnostního výběru. * Replikace (opakování) – vícenásobné opakování měření umožní posoudit náhodnou variabilitu měřených veličin, a tím i určit přesnost měření. * Blokový design, stratifikace – rozdělení experimentálních jednotek do bloků či strat, které vykazují podobné vlastnosti, umožní redukovat vliv zdrojů variability, které nejsou předmětem zkoumání. * Faktoriální uspořádání – experiment může zkoumat vliv několika faktorů (různých intervencí) naráz, včetně jejich synergických efektů. * Ortogonalita – faktoriální experiment má být navržen tak, aby umožňoval posoudit nezávisle vliv každého jednotlivého faktoru. On nomme plan d'expériences (en anglais, design of experiments ou DOE) la suite ordonnée d'essais d'une expérimentation, chacun permettant d'acquérir de nouvelles connaissances en maîtrisant un ou plusieurs paramètres d'entrée pour obtenir des résultats validant un modèle avec une bonne économie de moyens (nombre d'essais le plus faible possible, par exemple). Un exemple classique est le « plan en étoile » où en partant d'un jeu de valeurs choisi pour les paramètres d'un essai central, on complète celui-ci par des essais où chaque fois un seul des facteurs varie « toutes choses égales par ailleurs ». Un type de plan plus exhaustif est le plan factoriel consistant à choisir des valeurs pour chacun des facteurs en faisant varier simultanément tous les facteurs (de façon exhaustive ou non). Le nombre d'essais peut alors devenir très grand (explosion combinatoire). 실험계획법(實驗計劃法, design of experiments, DOE)은 효율적인 실험 방법을 설계하고 결과를 제대로 분석하는 것을 목적으로하는 통계학의 응용 분야이다. 로널드 피셔가 1920년대에 농업 실험에서 영감을 얻어 발전시켰다. 이후 의학, 공학, 실험 심리학과 사회학에 널리 적용되었다. 또한 마케팅 등에서 콘조인트 분석도 사용된다.
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