Google Data Analytics Professional Certification Practice Test

What does the term statistically significant mean?

1. The results are consistent and reliable

2. The results are caused by random chance

3. The sample size is larger

4. The data has been replicated successfully

The correct answer is: The results are consistent and reliable

The term statistically significant refers to a situation in which the results of a study or experiment are unlikely to have occurred by random chance. When results are deemed statistically significant, it indicates that the data reveals an effect or relationship that is strong enough to be considered reliable and not due to mere coincidence. This concept is crucial in data analysis, as it helps researchers to understand whether their findings reflect real-world phenomena or if they are likely the result of random fluctuations in the data. While it’s true that consistency and reliability in results contribute to the robustness of a study's findings, statistically significant results specifically focus on the probability that the observed effects arise from factors other than random chance. Therefore, the goal when assessing statistical significance is to determine the likelihood of an observed result occurring by chance and ensuring that it has practical implications in a broader context. The other options, while they pertain to aspects of data analysis, do not directly define what statistically significant means. For instance, simply having a larger sample size does not guarantee significance; it may enhance the reliability of results but doesn’t inherently indicate that the observed results are true indicators of underlying trends or effects. Similarly, replication of data or results can support findings but isn't synonymous with the concept of statistical significance itself.