Skip to main content
Back

Two-Way ANOVA - Excel definitions

Control buttons has been changed to "navigation" mode.
1/15
  • Two-Way ANOVA
    Statistical method for comparing means across two factors, allowing assessment of their individual and combined effects.
  • Interaction Effect
    Phenomenon where the influence of one factor depends on the level of another, complicating interpretation of mean differences.
  • Factor
    Categorical variable whose levels are used to group data for comparison in ANOVA analyses.
  • Level
    Distinct category within a factor, such as types of advertising or discount percentages.
  • Null Hypothesis
    Default assumption stating no interaction or difference in means between groups or factors.
  • Alternative Hypothesis
    Statement suggesting the presence of interaction or differences in means among groups or factors.
  • P-Value
    Probability measure used to determine statistical significance; compared to alpha to guide hypothesis decisions.
  • Alpha
    Threshold for statistical significance, commonly set at 0.05, guiding whether to reject the null hypothesis.
  • Replication
    Design feature in ANOVA where multiple observations are collected for each combination of factor levels.
  • Source of Variation
    Component in ANOVA summary tables identifying where differences in data arise, such as factors or interaction.
  • F Statistic
    Ratio used in ANOVA to compare variance between groups to variance within groups, indicating significance.
  • Data Analysis Toolpak
    Excel add-in providing automated statistical calculations, including ANOVA summary tables.
  • Summary Table
    Output in ANOVA displaying statistics for each factor, interaction, and overall variation.
  • Advertising Medium
    Example factor in business analytics, with levels such as social media, TV, and email.
  • Discount Level
    Example factor representing different price reductions, such as none or 20%.