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Statistical Model Building and Design of Experiments
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Abstract
Topics covered in this module include
- Quantification of Uncertainty in Experimental data and impact on model analysis using Probability Theory
- Review of Statistics for building Statistical Models (Multilinear Regression analysis)
- Design of Experiments for Building Statistical models
- Single factor Experiments
- Multifactor Experiments
- Factorial Experimentation
- Fractional Factorial Experimentation
- Response Surface Modeling
- Process Optimization
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| Lecture Number/Topic | Online Lecture | Video | Lecture Notes | Supplemental Material | Suggested Exercises |
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| Introduction to Model Building | View Flash | Notes (ppt) | |||
| Course Background:
Initial ideas developed for Pharmaceutical Scientists at the Dow Chemical Plant in Brindisi, Italy (1975)
Subsequently evolved into a global course on Process Optimization... |
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| Probability Theory Review | Notes (ppt) | ||||
| For any real system or phenomenon, there will be a certain amount of variability associated with data generated by the system.
Probability is the language used to characterize and interpret the... |
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| Review of Statistics | Notes (ppt) | Example 1 Instructions Example 1 JMP Data Example 2 Instructions Example 2 JMP Data Example 3 Instructions Example 3 and 4 JMP Data Example 4 Instructions Example 5 Instructions Example 5 JMP Data Example 6 Instructions Example 6 JMP Data Example 7 Instructions Example 7 JMP Data |
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| This lecture covers the following topics
Difference between statistics and probability
Statistical Inference
Samples and populations
Intro to JMP software package
Central limit... |
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| Single Factor Experiments | Notes (ppt) | Example 1 Instructions Example 1 JMP Data Example 2 JMP Data Example 3 JMP Data Example 4 JMP Data Example 5 JMP Data |
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| The purpose of single factor experiments is to:
Quantify relationship between a single factor and a single measured or response variable
Compare the relative effectiveness of two or more... |
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| Factorial Experimentation | Notes (ppt) | Example 1 Instructions Example 1 Data |
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| A full factorial experiment is a set of experimental runs such that all levels of a given factor are combined with all levels of every other factor. |
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| Screening | Notes (ppt) | Example 1 JMP Data Example 2 JMP Data Example 3 JMP Data |
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| The objectives of this lecture are to:
Show how to screen or select the most important main effects with fewer experiments.
Show how to construct fractional factorial experiments by... |
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| Response Surface Methodology | Notes (ppt) | Example 1 Instructions Example 1 JMP Data Example 2 JMP Data |
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| This lecture describes response surface models:
Models are simple polynomials
Include terms for interaction and curvature
Coefficients are usually established by regression analysis with... |
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| Problems for Statistical Model Building | Scenarios |
Problem Statement Problem 1 JMP Data Problem 2 JMP Data Problem 3 JMP Data Problem 4 JMP Data Problem 5 JMP Data Problem 7 JMP Data Problem 8 JMP Data Problem 9 JMP Data Problem 10 JMP Data Problem 11 JMP Data Problem Solution | |||
| Scenarios, problem statements, JMP data files, and solutions for the course on Statistical Model Building and Design of Experiments. Scenario 1 is based on a batch reactor system for small molecule... |
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