Chapter 9: Sampling in Quantitative Research

Population

The entire set of units from which the sample is drawn, not limited to people but including entities like nations, cities, firms, etc.

Sample

A subset of the population chosen for investigation, selected through probability or non- probability methods.

Sampling Frame

A comprehensive list of all population units from which the sample is drawn.

Representative Sample

A sample that accurately mirrors the population, serving as a microcosm of it.

Sampling Bias

Distortion in sample representativeness, with some groups over-represented and others under-represented.

Probability Sample

A sample selected using random methods, aiming to minimize sampling error.

Non-probability Sample

A sample not chosen through random selection, leading to potential bias.

Sampling Error

The discrepancy between the sample and population characteristics, even in probability samples

Non-sampling Error:

Differences due to deficiencies in sampling or issues like poor question wording and non-response.

Non-response

A source of non-sampling error when some sample members refuse to cooperate or cannot be contacted

Census

Data collection from an entire population, which can refer to national censuses but has a broader statistical meaning.