Final answer:
A finding of statistically significant differences between study groups indicates that the differences are not due to random chance, suggesting a real effect of the variable or treatment being tested. A level of significance, such as 5% or 1%, is used to determine the threshold for statistical significance.
Step-by-step explanation:
When a team of researchers finds statistically significant differences between their study groups, it means they have found evidence strong enough to conclude that the differences in their data are not due to random chance. This suggests that the observed differences are likely because of the variable or treatment being tested.
For example, if researchers are analyzing the effectiveness of a new drug, they would use statistical tests to compare outcomes between the experimental group (those receiving the drug) and the control group (those not receiving the drug). A finding of statistical significance at a 10 percent level or lower commonly indicates that the drug has had an effect. The level of significance is the threshold for determining whether a result is statistically meaningful; commonly used levels are 0.05 (5%) and 0.01 (1%). If the obtained p-value is less than the level of significance, it supports the conclusion of a significant effect.
It is crucial for experimenters to consider ethical constraints, control for lurking variables, which can influence results and to be cautious in the conclusions they draw from their tests, only asserting what the data can robustly support.