JMP Certified Associate: Statistical Thinking for Industrial Problem Solving
During this performance-based examination, candidates will apply the skills and knowledge necessary to apply statistical thinking and fundamental statistical methods to solve industrial problems.
Successful candidates should have the ability to:
- Explain the importance of using data and applying statistical methods to solve problems.
- Develop a clearly defined problem statement to translate a business problem into an analytics problem
- Compile and prepare data for analysis.
- Visually and interactively explore data to identify potential root causes of variation.
- Translate analytics results into an actionable decisions and results.
- Interpret the components of a control chart to determine if a process is stable.
- Design a measurement system analysis (MSA) and interpret the results of an MSA.
- Conduct a capability analysis and interpret Cp, Cpk, Pp and Ppk.
- Interpret statistical intervals and hypothesis test results.
- Describe the impact of sampling and sample size on statistical decision making.
- Explain the difference between correlation and causation.
- Fit a simple regression model and interpret the results.
- Interpret analysis results for multiple linear regression and binary logistic regression.
- Explain the importance of DOE in developing knowledge of cause and effect.
Exam Content & Pricing
Candidates who earn this credential will have earned a passing score on the Statistical Thinking for Industrial Problem Solving exam.
- 55-60 multiple-choice questions
- Passing score is 725; uses a score range from 200 to 1,000 points. For more information about scaled scores see our FAQ.
- 150 minutes to complete exam.
- Use exam ID A00-910; required when registering with Pearson VUE.
- Candidates will use JMP 15 software to perform this exam
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