Hello everyone, today I’m discusing about Anova test.

To ascertain whether there are statistically significant differences between two or more groups, the means of the groups are compared using the Analysis of Variance (ANOVA) statistical test

The Analysis of Variance (ANOVA) statistical test compares the group means to determine if there are any statistically significant differences between two or more groups.

ANOVA comes in a variety of forms, including:

When you have one independent variable with two or more levels or groups, you utilize the one-way ANOVA. It investigates whether the group means differ in any notable ways.

The two-way ANOVA is an extension of the one-way ANOVA that looks at the interactions and impacts of two independent variables (factors) on the dependent variable. It can assist you in determining whether the two elements’ individual impacts are accompanied by any interactions.

Three-Way ANOVA and Higher-Way ANOVA: When your study design involves numerous elements, you can utilize ANOVA with more than two independent variables.

The variance within groups is compared to the variance between groups to determine how the ANOVA test operates. You can conclude that there are significant differences between the groups if the variation between them is significantly greater than the variation within them. An F-statistic is commonly used to express the outcome, and a p-value is used to assess the significance level.

You would reject the null hypothesis and conclude that there are significant differences between the groups if the p-value is less than the selected significance level (e.g., 0.05). Post-hoc tests (such as the Bonferroni or Tukey’s HSD tests) are frequently employed to identify the precise group differences that are significant.

 

When analyzing data from surveys, experiments, and studies that look at several components, ANOVA is frequently employed in both experimental and observational research.