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Experimental Design: Principles and Applications

Explore the key elements and principles of experimental design in this summary of Chapter 10 from Larry Gonick's 'The Cartoon Guide to Statistics'. Learn about experimental units, treatments, local control, randomization, replication, and the use of ANOVA in analyzing complex designs.

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Experimental Design: Principles and Applications

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  1. Chapter 10 Experimental Design Summary of Chapter By James Valenza GEOG 3000

  2. Experimental Design • The following slides will contain theoretical material pertaining to the Experimental Design Process as seen in Chapter 10 of Larry Gonick’s ‘The Cartoon Guide to Statistics’

  3. Elements of a Design • There are two basic elements of a design. • Experimental Units • Treatments (assigned to the units)

  4. Elements of a Design cont… The objective of any Experimental Design is to Compare the Treatments. An example would be to testing new fertilizers for corn crops. In this case, the Experimental Units would be the different plots within the experimental area, while the Treatments would be the different fertilizers used.

  5. Why Use Experimental Design? Because we are concerned with the analysis of data generated from an experiment.

  6. Industries in which Experimental Design Process is used. To name a few………. • Agriculture • Medicine • Social Sciences • Industrial Processes

  7. Principles of Experimental Design 3 Basic Principles… • Local Control • Randomization • Replication

  8. Local Control Local Control refers to any method that accounts for and reduces natural variability. One way is to group similar experimental units into blocks. (Gonick, pg.183) Lack of controls can lead to experimental bias, the favoring of certain outcomes over others.

  9. Randomization Randomization is an extremely important step in statistics. Because it is generally extremely difficult for experimenters to eliminate bias using only their expert judgment, the use of randomizationin experiments is common practice. In a randomized experimental design, objects or individuals are randomly assigned (by chance) to an experimental group. Using randomization is the most reliable method of creating homogeneous treatment groups, without involving any potential biases or judgments. (Yale, 1997)

  10. Replication To improve the significance of an experimental result, replication, the repetition of an experiment on a large group of subjects, is required. If a treatment is truly effective, the long-term averaging effect of replication will reflect its experimental worth. Replicationreduces variability in experimental results, increasing their significance and the confidence level with which a researcher can draw conclusions about an experimental factor.

  11. Supplemental Material • The following was not covered in this chapter but I would briefly like to touch upon ANOVA • ANOVA- Analysis of Variance (is used as a model to for analyzing complex experimental designs)

  12. ANOVA There are two types of ANOVA tests: 1-way ANOVA- Divides the variance into 2 parts Treatment Error • 2-way ANOVA- Divides the variance into 4 parts • Row Effect • Column Effect • Interaction Effect • Error

  13. ANOVA cont… Example of 1-way ANOVA Test

  14. Resources • Khan Academy http://www.Khanacademy.org/ • Yale Department of Statistics, 1997 • http://www.stat.yale.edu/Courses/1997-98/101/expdes.htm • Weiss, Neil. Introductory Statistics: 8th Edition, 2008. Pearson Education Inc. • Wikipedia http://www.wikipedia.org

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