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After rigorous statistical analyses have shown a very low likelihood (usually 5% out less) of a result having occurred by chance alone, the result is said to be



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Answer and Explanation: Statistically significant. The rigorous statistical analysis used in many cases is a test known as the chi-square test. This test is responsible for determining the likelihood that the results of an experiment are due to chance. By extension, it also helps determine the validity of experimental results.

After the calculations are completed, the value is compared to a p-value chart. If the p-value is less than 0.05, it indicates that there is a 5% chance or less that the experimental values were due to chance alone. Usually, this low of a percentage indicates that the data is statistically significant. However, if the p-value is greater than 0.05, then it means that there is a greater than 5% chance that the experimental results are due to chance alone. As a result, the experimental results can't be deemed statistically significant or conclusive in terms of proving a hypothesis.