Two-Way Anova

EXAMPLE:

Sport clothing company would like to check if number of running sessions depends on gender and weather temperature.

HYPOTHESIS:

STEP I : State the null and research hypotheses.
A two-way ANOVA with replication tests three null hypotheses:
  • H1: Both genders have equal amount of running sessions on the average.
  • H2: All of the temperatures have equal amount of running sessions on the average.
  • H3: Two factors are independent or that interaction effect is not present.

    STEP II : Level of significance.

    alpha = 0.05

    TESTING:

    Two-Way Anova will compare amount of running sessions between genders and weather temperature.

    RESULTS:

    Significance for Gender is = .006
    P-value is less then .05 which means that there is a statistically significant interaction effect.

    Sig. of interaction: Temperature * Gender = .037
    Sig < alpha .05

    EXPLANATION:


    The number of running session based on gender is influenced by weather temperature. Two factors are not independent.