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Statistical Model Building and Design of Experiments

By Gary Blau

Purdue University

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 …

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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
    1. Single factor Experiments
    2. Multifactor Experiments
    3. Factorial Experimentation
    4. Fractional Factorial Experimentation
    5. Response Surface Modeling
    6. Process Optimization
Cite this work

Researchers should cite this work as follows:

  • Gary Blau (2008), "Statistical Model Building and Design of Experiments," http://pharmahub.org/resources/145.

    BibTex | EndNote

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  1. Statistical model building

Supporting Documents

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Lecture Number/Topic Breeze Video Lecture Notes (PDF) Supplemental Material Suggested Exercises
Introduction to Model Building
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 …		 View Notes
Probability Theory Review
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 …		 Notes
Review of Statistics
This lecture covers the following topics Difference between statistics and probability Statistical Inference Samples and populations Intro to JMP software package Central limit …		 Notes 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
Single Factor Experiments
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 …		 Notes Example 1 Instructions
Example 1 JMP Data
Example 2 JMP Data
Example 3 JMP Data
Example 4 JMP Data
Example 5 JMP Data
Factorial Experimentation
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.		 Notes Example 1 Instructions
Example 1 Data
Screening
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 …		 Notes Example 1 JMP Data
Example 2 JMP Data
Example 3 JMP Data
Response Surface Methodology
This lecture describes response surface models: Models are simple polynomials Include terms for interaction and curvature Coefficients are usually established by regression analysis with a …		 Notes Example 1 Instructions
Example 1 JMP Data
Example 2 JMP Data
Problems for Statistical Model Building
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 …		 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