First, let’s check that the predictor variable (elephant
) and the covariate (experience
) are independent. To do this we can run a one-way ANOVA. The output below shows that the main effect of elephant
is not significant, F(1, 118) = 1.384, p = 0.244, which shows that the average level of prior football experience was roughly the same in the two elephant groups. This result is good news for using this model to adjust for the effects of experience
.
The output below shows that the experience of the elephant significantly predicted how many goals they scored, F(1, 117) = 9.931, p = 0.002. After adjusting for the effect of experience, the effect of elephant is also significant. In other words, African and Asian elephants differed significantly in the number of goals they scored. The adjusted means tell us, specifically, that African elephants scored significantly more goals than Asian elephants after adjusting for prior experience, F(1, 117) = 8.589, p = 0.004.
The covariate, football experience, was significantly related to the how many goals were scored, F(1, 117) = 9.93, p = 0.002, = 0.069 (95% CI [0.008, 0.173]). The more prior football experience the elephant had, the more goals they scored in the season. African elephants scored significantly more goals than Indian elephants after adjusting for their experience, F(1, 117) = 8.59, p = 0.004,
= 0.059 (95% CI [0.004, 0.159]).