This is a basic course in designing experiments and analyzing the resulting data. The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Opportunities to use the principles taught in the course arise in all aspects of today’s industrial and business environment. Applications from various fields will be illustrated throughout the course. Computer software packages (JMP, Design-Expert, Minitab) will be used to implement the methods presented and will be illustrated extensively.
Este curso faz parte do Programa de cursos integrados Criação de experimentos
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oferecido por
Programa de cursos integrados Criação de experimentosUniversidade do Estado do ArizonaInformações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 1 de 4 no
Nível intermediário
Aprox. 13 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
O que você vai aprender
By the end of this course, you will be able to:
Approach complex industrial and business research problems and address them through a rigorous, statistically sound experimental strategy
Use modern software to effectively plan experiments
Analyze the resulting data of an experiment, and communicate the results effectively to decision-makers.
Habilidades que você terá
- statistical Methods for Process and Product improvement
- design of experiments
- experiment design
- designing experiments
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 1 de 4 no
Nível intermediário
Aprox. 13 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade do Estado do 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 - O que você aprenderá com este curso
4 horas para concluir
Unit 1: Getting Started and Introduction to Design and Analysis of Experiments
4 horas para concluir
6 vídeos (Total 54 mín.), 6 leituras, 2 testes
4 horas para concluir
Unit 2: Simple Comparative Experiments
4 horas para concluir
9 vídeos (Total 96 mín.), 1 leitura, 3 testes
3 horas para concluir
Unit 3: Experiments with a Single Factor - The Analysis of Variance
3 horas para concluir
10 vídeos (Total 84 mín.), 1 leitura, 2 testes
2 horas para concluir
Unit 4: Randomized Blocks, Latin Squares, and Related Designs
2 horas para concluir
6 vídeos (Total 52 mín.), 1 leitura, 2 testes
Avaliações
- 5 stars77,36%
- 4 stars15,78%
- 3 stars3,68%
- 2 stars1,05%
- 1 star2,10%
Principais avaliações do EXPERIMENTAL DESIGN BASICS
por DR25 de jul de 2020
It was a great experience while doing experimental design basics. I learned a lot about the Strategy of experimentation and basic statistical concepts.
por RC22 de nov de 2020
This was an excellent course that gave me knowledge in experimental design with which it is possible to apply to any industry or field.
por RZ12 de jan de 2021
pretty good course , it would have been great to have pdf or brief with the material, the book is great too , class notes would have been great.
por BA17 de dez de 2020
Very excellent presentation. I very much enjoyed doing the course.
Sobre Programa de cursos integrados Criação de experimentos
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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