Can the sample size exceed the sample size grid?

The assertion that the sample size can exceed the sample size grid is accurate because in various contexts, particularly in statistical sampling and survey methodology, flexibility exists beyond predefined parameters. The sample size grid often serves as a guideline based on factors like desired confidence levels and margins of error. However, researchers may encounter situations requiring a larger sample size to ensure sufficient power for detecting effects or to achieve more precise estimates.

This flexibility is particularly relevant when the initial survey objectives evolve or when there are practical considerations, such as increased variability in the population being studied or the need for stratified samples to ensure representation across different subgroups. In these cases, exceeding the sample size grid may yield more reliable and actionable results, allowing for a deeper understanding of the population and improving the robustness of the findings.

While other choices suggest constraints, such as restrictions on size without approvals or in specific situations, these do not account for the inherent adaptability researchers may have in adjusting sample sizes based on their analytical needs and study design considerations. Thus, flexibility in sample size allows for the pursuit of more comprehensive and nuanced data collection.