The P-value for the blocking variable (0.00) is smaller than the significance level (0.05),.Than the significance level, we accept the null hypothesis when it is smaller, we reject it. The null hypothesis that the blocking variable (IQ) had no effect on the dependent variable (test score).Įach P-value (shown in the last column of the ANOVA table) is the probability that an F statistic would be more extreme (bigger) than theį ratio shown in the table, assuming the null hypothesis is true.Statistical Significanceįor this study, analysis of variance tested two hypotheses: Recall that the researchers undertook this study to answer two questions:Īnswers to both questions can be found in the ANOVA summary table. How strong is the effect of teaching method on the student performance?.Does teaching method have a significant effect on student performance (as measured by test score)?.In conducting this experiment, the researcher has two research questions: Within each block, each student is randomly assigned to a different teachingĪt the end of the term, the researcher collects one test score (the dependent variable) from each subject, The researcher assigns subjects to six blocks of three, such that students within the same block have the The researcher selects subjects randomly from a student population. RUNNING ANOVA XLSTAT HOW TOTo demonstrate how to conduct analysis of variance for a randomized block experiment with Excel, we'll work through a real-world problem.Īs part of a randomized block experiment, a researcher tests the effect of three teaching methods
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