Answer:
Convenience sampling can yield biased search results, because it produces lack of information, so we can’t generalize results with <em>statistical accuracy</em>.
Explanation:
This technique is very common and consists of selecting a population sample that is accessible. That is, the individuals are selected because they are readily available, not because they were selected using a statistical criterion. This convenience generally represents <em>greater operational ease</em> and <em>low sampling cost</em>, but results in the inability to make general statements with statistical accuracy about the population.
This type of sampling is used when <em>we don't have access to the complete list of individuals that make up the population</em> (sampling frame), so we don't know the probability that each individual will be selected for the sample. The main consequence of this lack of information is that we can't generalize results with <em>statistical accuracy</em>.
The most obvious criticism of convenience sampling is sampling bias and that the sample is not representative of the entire population.