Location

Productivity and Quality Institute - Alexandria

Objectives

• Course Objectives for "Statistical Design and Analysis of Experiments":1. Understand the principles of experimental design, including randomization, replication, and blocking, to ensure valid statistical inference.2. Gain proficiency in designing experiments to investigate relationships between variables and to optimize processes.3. Develop skills in selecting appropriate statistical methods for analyzing experimental data, including ANOVA, regression analysis, and factorial designs.4. Learn how to interpret and communicate results effectively, including drawing conclusions and making recommendations based on experimental findings.5. Apply statistical software tools such as R or SAS to conduct analyses and visualize data, enhancing both analytical skills and practical experience.

Outcomes

• Understand the fundamental principles of experimental design, including randomization, replication, and blocking, and their role in ensuring valid and reliable statistical inference.• Demonstrate proficiency in selecting appropriate experimental designs for different research questions and situations, considering factors such as experimental objectives, resources, and potential sources of variability.• Apply statistical techniques for the analysis of experimental data, including analysis of variance (ANOVA), regression analysis, and factorial designs, to draw meaningful conclusions and insights from experimental results.• Interpret and critically evaluate experimental findings, including assessing the significance of treatment effects, identifying interactions between factors, and understanding the limitations and assumptions underlying statistical models.• Communicate effectively about experimental design and analysis, both orally and in writing, by presenting results, interpre

Course Contents

1. Introduction to the Design of Experiments (DOE): concept, steps, pre-requisites.2. Types and applications of different experimental designs.3. Selection criteria of the appropriate design of experiments.4. Single factor completely randomized design.5. Modeling the results of the design of experiments.6. Block randomized designs.7. Basic Definitions: Randomization, Replications, Blocking, Confounding and Aliasing8. Full factorial Designs versus OFAT approach.9. 2k Factorial Designs.10. Fractional Factorial Designs.11. Simple Linear Regression and Analysis of Residuals.12. Actual case studies discussion.