Chamberlain's Law is a principle in the field of statistics that states that the more data points you have, the more likely the average of those points will reflect the true average of the entire population. This concept emphasizes the importance of sample size in research and data analysis, suggesting that larger samples yield more reliable results. The law is named after W. Lawrence Chamberlain, who highlighted this relationship in his work. It serves as a reminder for researchers to consider the size of their data sets when drawing conclusions, as small samples can lead to misleading interpretations of the data.