How does increasing sample size in random sampling affect the results?

Increasing the sample size in random sampling can improve the reliability of the data collected for several reasons. Firstly, a larger sample size typically reduces the impact of random errors and anomalies that can occur in a smaller sample. This leads to results that are more representative of the entire population.

Additionally, with more data points, the statistical analyses conducted on the results can yield more precise estimates and tighter confidence intervals. This means that the conclusions drawn from the sample are likely to be closer to the true values within the whole population, enhancing the overall validity of the study's findings.

Furthermore, as sample size increases, the variability in the data tends to decrease, making it easier to detect true trends and patterns in the dataset. Therefore, opting for a larger sample size is a fundamental practice in statistical research to enhance the robustness and reliability of the conclusions drawn from the data.