690 Sample Size Calculator
Based on the provided sample size of 690, I'll create a comprehensive table with key information about this sample size and related statistical concepts. Here's what you need to know:
| Aspect | Details |
|---|---|
| Sample Size | 690 |
| Significance Level | Typically 0.05 (5%) |
| Power | Typically 0.8 (80%) |
| Effect Size | Cohen's d (0.2 small, 0.5 medium, 0.8 large) |
| Margin of Error | Typically 5% |
| Confidence Level | Usually 95% (z-score = 1.96) |
| Population Size | Assumed to be large or unknown |
| Estimated Prevalence | Varies depending on the study (often 50% if unknown) |
Interpretation of Sample Size
A sample size of 690 is considered relatively large for many studies. This sample size can provide several advantages:
- Precision: A larger sample size generally leads to more precise estimates of population parameters1.
- Statistical Power: With 690 participants, the study likely has good statistical power to detect even small to medium effect sizes.
- Confidence Intervals: This sample size should produce narrower confidence intervals, indicating more precise estimates2.
- Generalizability: A larger sample is more likely to be representative of the population, enhancing the study's external validity.
- Subgroup Analysis: With 690 participants, there may be sufficient numbers to perform meaningful subgroup analyses.
Considerations
When working with a sample size of 690, keep in mind:
- Resource Allocation: Ensure that you have adequate resources to handle data collection and analysis for this many participants.
- Statistical Significance vs. Practical Significance: With a large sample, even small differences may be statistically significant. Always consider the practical significance of your findings3.
- Sampling Method: The method used to select these 690 participants is crucial for the validity of your results. Ensure that your sampling strategy is appropriate for your research questions.
- Attrition: Plan for potential dropouts or incomplete data, especially in longitudinal studies.
- Effect Size: While this sample size is good for detecting medium to large effects, it may still be challenging to detect very small effects reliably.
Remember that while 690 is a good general sample size, the ideal sample size can vary depending on the specific research question, study design, and statistical analyses planned. Always consult with a statistician or use appropriate sample size calculation tools for your particular study needs.