I can help you conduct statistical analysis and reporting using JMP
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Project Details
Why Hire Me?
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With over 7 years of experience using JMP, I offer a data analysis approach that balances technical accuracy with clarity and storytelling.
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Proficient in hypothesis testing, regression, ANOVA, and predictive modeling using JMP
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Skilled in JMP’s interactive dashboards, exploratory tools, and quality control features
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Adept at translating statistical outputs into actionable narratives for both technical and non-technical stakeholders
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Experienced in working with academic, manufacturing, healthcare, and business datasets
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Can incorporate JMP into Lean Six Sigma or Design of Experiments (DOE) workflows
What I Need to Start Your Work
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Project Details
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Project objectives, target questions, or hypotheses
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Context (e.g., academic study, industry use case, quality control initiative)
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Data Files
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Dataset in
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Description of variables, units, and any prior data cleaning
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Specific Requirements
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Required analyses (e.g., predictive modeling, ANOVA, control charts)
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Any mandatory tools or techniques (e.g., Fit Model, Graph Builder, DOE)
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Reporting Instructions
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Report format (PDF, Word, or JMP output with annotations)
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Preferences for visualizations, styling, or formatting
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Communication & Timeline
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Preferred communication mode (email, call, etc.)
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Any specific deadlines or review milestones
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Portfolio
Customer Satisfaction Analysis Using JMP for a National Retail Chain
Used JMP to analyze customer survey data from over 10,000 responses, uncovering key predictors of satisfaction and visualizing demographic segments for targeted service improvements.
Process Optimization in Manufacturing Using JMP DOE and Control Charts
Deployed JMP's Design of Experiments (DOE) and SPC tools to identify optimal production settings, reduce defect rates by 38%, and standardize process control in a medium-scale manufacturing plant.
Predictive Maintenance Dashboard Using JMP for an Industrial Equipment Supplier
A leading supplier of industrial-grade compressors and hydraulic systems wanted to implement predictive maintenance strategies to reduce unexpected equipment failures at client sites.
Process






