**Table Results: A Comprehensive Overview of Key Data Points**

In recent research, a comprehensive table was compiled to summarize key data points, offering a clear and concise overview of findings. This table, comprising mean, standard deviation (SD), confidence interval (CI), p-value, and sample size, provides essential insights into the study's results.

**Mean**

The mean value represents the average outcome measured in the study. For instance, if the mean score on a psychological test was 75, it indicates the central tendency of the data. This metric is crucial for understanding the general magnitude of the effect or outcome.

**Standard Deviation (SD)**

The standard deviation quantifies the spread of the data around the mean. A low SD, such as 5, suggests that most scores fall within 5 points of the mean, indicating consistency. Conversely, a high SD, say 15, indicates greater variability, highlighting potential outliers or a broader range of responses.

**Confidence Interval (CI)**

The confidence interval offers a range within which the true population mean is likely to fall, with a specified level of confidence, typically 95%. For example, a CI of 70 to 80 at a 95% confidence level implies that we are confident the true mean lies within this range, reflecting the precision of our estimate.

**P-value**

The p-value assesses the statistical significance of the results. A p-value less than 0.05 (e.g., 0.03) indicates a statistically significant difference, suggesting that the observed effect is unlikely due to chance. This is critical for interpreting whether the results are meaningful beyond mere random variation.

**Sample Size**

The sample size, such as 100 participants, determines the study's generalizability. A sufficiently large sample ensures that findings are representative of the population and increases the study's reliability. Smaller samples may yield less precise estimates and higher sampling error.

**Conclusion**

This table elucidates the study's findings, emphasizing the importance of each metric. The mean provides the central tendency, SD and CI offer variability insights, the p-value assesses significance, and the sample size ensures representativeness. Together, these elements collectively offer a holistic view of the research outcomes, aiding in their interpretation and application.