Final answer:
Large sample size and random sampling reduce unusual responses and variability, providing a more accurate representation of the population and increasing survey reliability.
Step-by-step explanation:
Having a large sample size and utilizing random sampling help reduce the impact of unusual responses and sampling variability, leading to a more accurate representation of the population. When a sample is too small or not randomly selected, the results may not reflect the true characteristics of the population being studied. Larger samples reduce the likelihood that the sample is skewed by outliers, as they are more likely to contain a proportionate mix of different groups within the population. Random sampling ensures that every individual has an equal chance of being selected, providing each segment of the population with fair representation in the results. This methodology increases the reliability of the conclusions drawn from the survey data. On the contrary, when the sample size reaches a sizeable number that adequately represents the population, further increase in sample size yields only minor improvements in accuracy at higher costs, hence, reaching the balance between sample size and cost-effectiveness is also important.