SASInstitute A00-909 Exam Information and Actual Questions

  • Exam Code/Number: A00-909
  • Exam Name/Title: Design and Analysis of Experiments using JMP 14
  • Certification Provider: SASInstitute
  • Corresponding Certification: SASInstitute Certification

A00-909
FREE EXAM DUMPS QUESTIONS & ANSWERS

SASInstitute
A00-909 Exam
Design and Analysis of Experiments using JMP 14

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SASInstitute A00-909 Exam Overview:

Certification Vendor:SAS Institute
Exam Name:Design and Analysis of Experiments using JMP 14
Exam Number:A00-909
Available Languages:English
Exam Format:Multiple choice
Related Certifications:JMP Scripting Using JMP 14
Statistical Thinking for Industrial Problem Solving
Exam Way:Onsite/On-Demand at Pearson VUE
Official Syllabus URL:https://www.sas.com/en_gb/certification/exam-content-guides/jmp-design-analysis-experiments.html

SASInstitute A00-909 certification exam is designed for professionals who want to validate their knowledge and skills in designing and analyzing experiments using JMP 14 software. A00-909 exam is ideal for individuals who work with data and want to enhance their abilities in statistical analysis, experimental design, and data visualization. The A00-909 certification exam is a globally recognized certification that demonstrates your proficiency in JMP 14 software and your ability to design and analyze experiments using statistical methods.

The A00-909 exam is intended for individuals who have a strong background in statistics and data analysis, as well as experience using JMP. It is also recommended that candidates have at least two years of experience working with statistical data analysis in a professional setting. A00-909 exam is aimed at professionals who are looking to enhance their skills and knowledge in using JMP for experimental design and analysis.

SASInstitute A00-909 Exam Syllabus Topics:

SectionWeightObjectives
Create the next Experiment15%- Conduct verification to determine augmentation need
- Augment a design and define replicate, center points, axial, fold over
Data Collection15%- Replication vs multiple measurements
- Evaluate measurement system signal to noise ratio
- Benefits and impact of randomization
- Determine blocking requirements
Create a DOE Plan40%- Identify and define factors to vary in the experiment
- Identify and implement factor constraints
- Select terms to include in the model
- Create a design with appropriate features
- Identify and define critical responses to be measured
- Evaluate design performance for estimation, testing, prediction
Analysis30%- Use profiler under graph menu for prediction formulas
- Fit separate or combined models for multiple responses
- Exploit the best model
- Select the best model


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