Final answer:
The reliability of experimental results in the context of statistical significance is greatly influenced by the sample size. Large sample sizes reduce sampling variability and enhance the reliability and generalizability of the statistical conclusions.
Step-by-step explanation:
In the context of statistical significance, a crucial factor that contributes to the reliability of experimental results is sample size. Larger sample sizes tend to reduce sampling variability, which is the amount of variation in a statistic from one sample to another within a population. The larger the sample size, the smaller the variability between samples, making the statistic more reliable.
Adequate sample size helps ensure that the results are more likely to be true of the general population, beyond just the sample studied. In hypothesis testing, using a large sample size helps us achieve more robust and generalizable conclusions about the population being studied. It is critical for experiments and investigations to have a sufficient sample size to draw meaningful conclusions and to increase the credibility of the statistical analysis.