How does sample size affect the reliability of experimental results?

How does sample size affect the reliability of experimental results?

• A. Larger sample sizes often decrease statistical power
• B. Sample size does not affect the reliability of results
• C. Larger sample sizes generally enhance reliability of results
• D. Smaller sample sizes are always more reliable

Answer: (C)

Larger sample sizes generally enhance the reliability of results because they reduce the impact of variability and increase the precision of estimates. In experimental research, a larger sample size allows for a more accurate reflection of the population being studied, leading to more generalizable findings. This is because larger samples tend to buffer against anomalies and outliers that can skew results, thereby providing a clearer picture of the underlying effects being measured. Additionally, larger samples can improve statistical power, which is the probability of detecting a true effect when it exists. This means that researchers are less likely to make Type II errors (failing to detect an effect that is actually there) when the sample size is sufficient. Overall, the increased reliability from larger sample sizes contributes to drawing more credible conclusions from experimental data.

Larger sample sizes generally enhance the reliability of results because they reduce the impact of variability and increase the precision of estimates. In experimental research, a larger sample size allows for a more accurate reflection of the population being studied, leading to more generalizable findings. This is because larger samples tend to buffer against anomalies and outliers that can skew results, thereby providing a clearer picture of the underlying effects being measured.

Additionally, larger samples can improve statistical power, which is the probability of detecting a true effect when it exists. This means that researchers are less likely to make Type II errors (failing to detect an effect that is actually there) when the sample size is sufficient. Overall, the increased reliability from larger sample sizes contributes to drawing more credible conclusions from experimental data.