Final answer:
A sampling method with too much bias leads to less accurate results because it does not represent the population equally, causing skewed conclusions.
Step-by-step explanation:
In the context of statistical analysis, when a sampling method exhibits too much bias, the impact on the results is that they will be less accurate. This is because a biased sample does not equally represent all members of the population, leading to incorrect or skewed conclusions. For example, conducting a survey of students only during a specific time frame, such as noon lunchtime, will miss out on those who are not available at that time, leading to a non-representative sample of the entire student population. Therefore, it is imperative that the sample is collected in a manner where each member of the population has an equally likely chance of being selected. Reliable statistical measures must account for the reliability and representativeness of the sample to ensure consistent and accurate results.