In: Economics
Convenience sample: The researcher chooses a sample that is readily available in some non-random way.
Example—A researcher polls people as they walk by on the street.
Why it's probably biased: The location and time of day and other factors may produce a biased sample of people.
In this case, researcher has used convenience sampling method. The results won't be accurate, because the researcher collected his sample according to his convenience not for the sake of the research.
For the effectiveness of this research, the data should be collected from women irrespective to their income. In malls there may be upper or middle class women. So for accurate results lower class people should also participate in the survey.
For that, stratified random sample is good.
Stratified random sample: The population is first split into groups. The overall sample consists of some members from every group. The members from each group are chosen randomly.
Example— In the survey, we can divide the women according to income and collect data for each and gather.
Why it's good: A stratified sample guarantees that members from each group will be represented in the sample, so this sampling method is good when we want some members from every group.