STAT235 Lecture Notes - Lecture 12: Total Variation, Standard Deviation, Test Statistic
28 Feb 2018
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The analysis of variance (anova) is a procedure to test the equality of three or more population means. In fact, we used anova for testing the null k. Note: the name of the test refers to comparing different sources of variability; it will test differences among means. We test h0: 1= 2 = 3 (all population means are equal) Ha: at least one of the means differs from the others. Ha: at least two population means are different. Necessary assumptions for one-way analysis of variance are: We have k independent random sample, one srs from each k populations. The data within each treatment group must be independent. The ith population has a normal distribution with unknown mean i where. All the populations have the same standard deviation . i=1,2, ,k. We assess mean differences by comparing the amount of variability explained by different sources. 5: variation among the means of samples (treatments)
