ANOVA

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Examples of when to use a one way ANOVA

Situation 1: You have a group of individuals randomly split into smaller groups and completing different tasks. For example, you might be studying the effects of tea on weight loss and form three groups: green tea, black tea, and no tea.

Situation 2: Similar to situation 1, but in this case the individuals are split into groups based on an attribute they possess. For example, you might be studying leg strength of people according to weight. You could split participants into weight categories (obese, overweight and normal) and measure their leg strength on a weight machine.

Data Analysis (Sample Result)

Null Hypothesis: There are no statistical differences among (Treatments), the samples come from the same population

Alternative Hypothesis: There are statistical differences among the (treatments), the samples come from a different population

Use a single factor 1- Way Analysis of Variance Test (ANOVA).

Results of ANOVA tests

P value

Accept or Reject

P < 0.05 indicate means the 2 groups significantly different reject null hypothesis

P > 0.05 means the 2 groups are not significantly different accept null hypothesis