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The best statement that defines statistical significance among the options provided is:

**"There is less than 5% probability of obtaining the observed results if the null hypothesis is true."**

### Explanation:
Statistical significance is generally defined by the probability that the observed result would occur if the null hypothesis were true. A result is considered statistically significant if this probability (the p-value) is lower than a predetermined threshold, often 5% (or 0.05). This implies that there's less than a 5% chance that the observed data would occur under the assumption that there is no effect or difference (the null hypothesis).

Would you like further details on this topic, or do you have any questions?

Here are some related questions to expand your understanding:

1. What is the null hypothesis in statistical testing?
2. How is the p-value calculated, and what does it represent?
3. What is the difference between statistical significance and practical significance?
4. Why is the 5% level often chosen as the threshold for statistical significance?
5. How can sample size affect statistical significance?

**Tip:** Remember that statistical significance does not imply practical importance; it only indicates that the result is unlikely due to random chance.

Which of the following statements best defines statistical significance?
1. The difference between the observed results and hypothesized results is unlikely to have occurred by chance alone.
2. The results are at least as extreme as the observed results if the null hypothesis is true.
3. There is less than 5% probability of obtaining the observed results if the null hypothesis is true.
4. There is no overlap between the values observed and the values expected under the null hypothesis.
5. The difference between the observed results and the hypothesized results is large.

Learn what statistical significance means in the context of hypothesis testing. This question focuses on the probability that observed results would occur under the null hypothesis and covers key concepts such as P-values and the 5% significance threshold. Suitable for Grades 11-12 and college students.

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