What This Document Is
This resource is an introduction to the principles and practices of experimental design – a crucial methodology within computer systems analysis and performance evaluation. It delves into the systematic approach of planning and conducting experiments to understand the relationships between different variables and their impact on system behavior. This isn’t simply about running tests; it’s about designing those tests strategically to yield meaningful and reliable results. The material is presented as a set of lecture slides from a graduate-level course at Washington University in St. Louis.
Why This Document Matters
This material is essential for students and professionals involved in system design, performance analysis, and research. Anyone tasked with optimizing system performance, comparing different configurations, or validating models will find this a valuable foundation. It’s particularly relevant when you need to move beyond guesswork and establish statistically sound conclusions about system characteristics. Understanding these concepts will empower you to design experiments that isolate key factors, minimize errors, and confidently interpret data. It’s useful for anyone needing to justify design choices with empirical evidence.
Common Limitations or Challenges
This introduction focuses on the *principles* of experimental design. It does not provide a step-by-step guide to conducting specific experiments within a particular system. It also doesn’t offer pre-built experimental setups or ready-made analysis tools. While it touches upon different design types, it doesn’t delve into the complex statistical calculations required for full data analysis. It assumes a basic understanding of statistical concepts and focuses on the conceptual framework.
What This Document Provides
* A foundational understanding of key terminology used in experimental design (factors, levels, response variables, etc.).
* An overview of common pitfalls to avoid when planning and executing experiments.
* A categorization of different experimental design approaches, outlining their strengths and weaknesses.
* Illustrative examples to demonstrate the application of these concepts to real-world scenarios, such as workstation design.
* Discussion of the importance of identifying and managing interactions between different variables.
