This link has been bookmarked by 10 people . It was first bookmarked on 04 Dec 2008, by Wesley Shu.
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13 Apr 14
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Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences between group means and their associated procedures (such as "variation" among and between groups), developed by R.A. Fisher. In the ANOVA setting, the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are equal, and therefore generalizes the t-test to more than two groups. Doing multiple two-sample t-tests would result in an increased chance of committing a type I error. For this reason, ANOVAs are useful in comparing (testing) three or more means (groups or variables) for statistical significance.
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21 Oct 13
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An attempt to explain the weight distribution by dividing the dog population into groups (young vs old)(short-haired vs long-haired) would probably be a failure
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An attempt to explain the weight distribution by (pet vs working breed)(less athletic vs more athletic) would probably be somewhat more successful (fair fit)
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An attempt to explain weight by breed is likely to produce a very good fit
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The analysis of variance provides the formal tools to justify these intuitive judgments
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result of the method is a judgment in the confidence in an explanatory relationship
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ANOVA is a particular form of statistical hypothesis testing
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In the typical application of ANOVA, the null hypothesis is that all groups are simply random samples of the same population.
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25 Apr 13
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d between groups), in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes t-test to more than two groups. Doing multiple two-sample t-tests would result in an increased chance of committing a type I error. For this reason, ANOVAs are useful in comparing (testing) three, or more means (groups or variables) for statistical significance.
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ANOVA is considered to be a special case of linear regression[63] [64] which in turn is a special case of the general linear model
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07 Feb 13
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09 Nov 12
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procedures
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10 Feb 12
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In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated procedures, in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes t-test to more than two groups. Doing multiple two-sample t-tests would result in an increased chance of committing a type I error. For this reason, ANOVAs are useful in comparing two, three, or more means.
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17 Feb 11
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04 Dec 08
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One-way ANOVA is used to test for differences among two or more independent groups. Typically, however, the One-way ANOVA is used to test for differences among at least three groups, since the two-group case can be covered by a T-test (Gossett, 1908).
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20 Jul 07
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