Many experiments involve factors whose levels are chosen at random. A well-know situation is the study of measurement systems to determine their capability. This course presents the design and analysis of these types of experiments, including modern methods for estimating the components of variability in these systems. The course also covers experiments with nested factors, and experiments with hard-to-change factors that require split-plot designs. We also provide an overview of designs for experiments with response distributions from nonnormal response distributions and experiments with covariates.
Este curso forma parte de Programa especializado: Diseño experimental
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Programa especializado: Diseño experimentalUniversidad del Estado de ArizonaAcerca de este Curso
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Fechas límite flexibles
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Curso 4 de 4 en
Nivel intermedio
Aprox. 9 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (europeo), Ruso (Russian), Inglés (English), Español (Spanish)
Qué aprenderás
Design and analyze experiments where some of the factors are random
Design and analyze experiments where there are nested factors or hard-to-change factors
Analyze experiments with covariates
Design and analyze experiments with nonnormal response distributions
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 4 de 4 en
Nivel intermedio
Aprox. 9 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (europeo), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad del Estado de Arizona
Arizona State University has developed a new model for the American Research University, creating an institution that is committed to excellence, access and impact. ASU measures itself by those it includes, not by those it excludes. ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it.
Programa - Qué aprenderás en este curso
4 horas para completar
Unit 1: Experiments with Random Factors
4 horas para completar
6 videos (Total 44 minutos), 5 lecturas, 3 cuestionarios
2 horas para completar
Unit 2: Nested and Split-Plot Designs
2 horas para completar
6 videos (Total 64 minutos), 1 lectura, 2 cuestionarios
3 horas para completar
Unit 3: Other Design and Analysis Topics
3 horas para completar
7 videos (Total 71 minutos), 1 lectura, 3 cuestionarios
Reseñas
- 5 stars75 %
- 4 stars10,71 %
- 3 stars14,28 %
Principales reseñas sobre RANDOM MODELS, NESTED AND SPLIT-PLOT DESIGNS
por ML25 de nov. de 2021
Comprehensive and practical course in the Design of Experiments specialization. Helps reinforce the need for a physical experiment to align with constraints on randomization.
por AA25 de sep. de 2020
THIS FULL COURSE WAS EXCELLENT. IT WILL HELP IN MY PROJECT. THANK YO DOCTOR MONTGOMERY SIR.
por RR25 de jul. de 2020
Very exhaustive information about random models and nested and split-plot designs. Thank you to Professor Douglas C. Montgomery and Coursera Team.
Acerca de Programa especializado: Diseño experimental
Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
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