I would agree with this statement since it represents one of the general rules of statistics. The idea behind it is that sampling error decreases as the sample size increases. It means that the census of the whole population would not be subject to the margin of error. This inverse relationship can be explained using a simple example and logic. For instance, a private investigator would make a better dossier on someone if he had more information in public records/databases and dedicated more time to surveillance. Thus, the more information is at hand, the more accurate results one will get.
Of course, the data should be appropriately collected and processed without misconceptions to hold this example. Although the given statement is true, researchers apply specific steps to reduce sample errors rather than expand the sample size. For example, they replicate their studies using multiple groups or apply random sampling. For that reason, the majority of surveys have about 1,000 respondents. It is expensive to improve standard error by increasing sample size; hence, researchers tend to calculate appropriate samples and apply high-reliability measures instead.