What conclusion can be drawn if the score is high enough in a statistical test?

A high score in a statistical test generally indicates that there is a statistically significant effect of the independent variable on the dependent variable. This means the results are not due to random chance, but rather show a measurable difference or relationship as a result of manipulating the independent variable. Statistical significance suggests that the observed effect is likely to exist in the population from which the sample was drawn, affirming the hypothesis being tested.

This conclusion is often supported by p-values or confidence intervals that suggest the results are beyond a certain threshold of probability (commonly p < 0.05), thereby reinforcing the validity of the findings. Such statistical tests may include t-tests, ANOVA, or chi-square tests, depending on the nature of the data and the specific hypotheses being assessed.