101A_ancova_lab_feb_17_11

# 101A_ancova_lab_feb_17_11 - ANCOVA LAB STATISTICS 101A...

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ANCOVA LAB STATISTICS 101A PROFESSOR ESFANDIARI The objective of this lab is to show you how to conduct and interpret the results of ANCOVA (analysis of covariance) The test of assumptions in ANCOVA, and Post-hocs in ACOVA. As we discussed in lecture, the major objective of ANCOVA is to reduce error variance through statistical control. In order to do this, we need to identify a covariate, or a potential confounding factor or extraneous variable, that is correlated with the outcome. The outcome scores are then adjusted for the effect of the covariate and ANOVA is performed on the scores that have been adjusted for the effect of the covariate. So basically ANCOVA is equivalent of ANOVA performed on scores that have been adjusted for the covariate. Another way to reduce error variance is through experimental control and that requires making the variable that we think affects the outcome a factor in the model. For instance, if we are examining the effect of two teaching methods on learning physics, but, we think prior knowledge of physics affects the outcome, then we can make prior knowledge of physics a factor in the experiment by dividing the participants into groups based on their prior knowledge of physics (example above and below the mean or median) and making it a factor in the experiment. In a national mathematics study the following data was collected on eighth grade students: Pretest score on arithmetic in percentages Posttest scores on arithmetic in percentages The level of emphasis that teacher placed on “understanding the nature of proof”. 1 = little emphasis, 2 = some emphasis, 3 = a lot of emphasis Research question: If we control for the effect of the pretest score on arithmetic, is there any relationship between the level of emphasis that the teacher plays on proof and score on arithmetic test. Let us first run a one-way anova without using pretest on arithmetic as a covariate and see if we get significant results:

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Table one: Between-Subjects Factors Value Label N emphasis on understanding the nature of proof 1 less emaphasis 345 2 average emphasis 93 3 more emphasis
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## This note was uploaded on 06/22/2011 for the course STAT 101 taught by Professor Esfandi during the Spring '11 term at UCLA.

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101A_ancova_lab_feb_17_11 - ANCOVA LAB STATISTICS 101A...

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