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Multiple Comparisons: Bonferoni Test definitions

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  • One-way ANOVA
    Statistical method for comparing means across three or more groups using variance analysis from group and error sources.
  • Null Hypothesis
    Assumption that all group means are equal, serving as the baseline for statistical testing in variance analysis.
  • Post Hoc Test
    Procedure applied after rejecting the baseline assumption to identify which group means differ significantly.
  • Bonferroni Test
    Pairwise comparison method that adjusts error rates by multiplying p-values or dividing significance level by the number of comparisons.
  • Mean Square Error
    Value from variance analysis representing within-group variability, used in calculating test statistics for comparisons.
  • Sample Size
    Count of observations in each group, influencing calculations for test statistics and degrees of freedom.
  • Degrees of Freedom
    Number derived from total observations minus groups, used in determining statistical significance and p-values.
  • Pairwise Comparison
    Analysis of differences between every possible pair of group means to pinpoint significant disparities.
  • T Score
    Statistic calculated from sample means, variability, and sizes, indicating the magnitude of difference between groups.
  • P Value
    Probability measure indicating the likelihood of observing a result as extreme as the test statistic under the baseline assumption.
  • Adjusted P Value
    Probability measure modified to account for multiple comparisons, controlling the overall error rate in the experiment.
  • Significance Level
    Threshold for determining statistical significance, often set at 0.05, compared against adjusted probability measures.
  • Bonferroni Correction
    Technique for controlling experiment-wide error by multiplying probability measures or dividing the threshold by the number of comparisons.
  • Combinatorial Function
    Mathematical operation used to calculate the number of possible pairs among groups for comparison purposes.
  • Alternative Hypothesis
    Statement asserting that at least one group mean differs, guiding the direction of statistical testing after baseline rejection.