Lab13_Split Plot Design and Repeated measure

# Lab13_Split Plot Design and Repeated measure - EXST 7015 -...

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EXST 7015 - Statistical Inference II, Fall 2011 Lab 11: Split-Plot Design with Repeated Measures OBJECTIVES: The objective of an experimental design is to provide the maximum amount of reliable information at the minimum cost. In statistical terms, the reliability of information is measured by the standard error of estimates (that is directly related with the population variance, inversely related to sample size). Properly applied experimental design may effectively reduce the population variance, and/or could structure data collection to reduce the magnitude of the experimental error. Usually data resulting from the implementation of experimental designs are described by linear model and analyzed by the analysis of variance. For the last couple of weeks, several types of experimental designs (RBD, Nested Design and Latin Square Design) have been practice. You are getting familiar with how to recognize the experimental design based on the data structure and write the linear model and construct ANOVA source table based on different experimental design. In this week’s lab, another type of experimental design, Split Plot Design , will be introduced. Split-plot experiments began in the agricultural industry. Because one factor in the experiment is usually a fertilizer or irrigation method, it can only be applied to large sections of land called whole plots. The factor associated with this is therefore called a whole plot factor (Factor A). Within the whole plot, another factor, such as seed variety, is applied to smaller

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## This note was uploaded on 12/29/2011 for the course EXST 7015 taught by Professor Wang,j during the Fall '08 term at LSU.

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Lab13_Split Plot Design and Repeated measure - EXST 7015 -...

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