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Description

Experimentation is central to all applied sciences. The goal of most is to create experiments that can answer your specific question and answer that question in a logistically efficient manner. The purpose of this course is to prepare students to lean and implement principles in sampling, experimental design, and statistical analysis of those designs. By the end of this course students will learn to 
  • Understand terminology and basic principles of experimental design
  • Recognize the design of experiments in the literature and generate a testable hypothesis
  • Become familiar with analyzing experiments in R
  • Generate experimental designs for Completely random, Randomized complete block and augmented designs
  • Analyze Completely random, Randomized complete block, split plot and augmented designs 
Prerequisites: Introductory Knowledge of R

Recommended Background: Have downloaded R and R-studio on to their laptop

Outline

Class 1: Introduction to Experiments
  • Introduction to R-markdown
  • What is an experiment?
  • How is data organized
  • Let’s pick the right analysis
Class 2: What is a basic Design
  • Introduction Completely Random Design
  • Analysis of a Completely Random Design
  • Introduction Randomized Complete Block Design
  • Analysis of a Randomized Complete Block Design
Class 3: What is a complex Design
  • Introduction Split Plot Design
  • Analysis of a Split Plot Design
  • Introduction Augmented Design
  • Analysis of a Augmented Design
Class 4: Matching Design to the Question
  • What is your Question?
  • What comparisons are relevant?
  • Which Design best fits your logistical constraints?
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