Quota Sampling

A second glaring weakness in local surveys is the extensive and general use of quota sampling to create a supposedly “representative sample” of the Philippine population. In quota sampling, survey respondents are picked from different types of people (e.g. by age, sex, religion, income) and various predetermined areas (e.g. region of country, as well as urban or rural).

This method is the most familiar form of non-probability sampling. It is supposed to mirror the same proportions in the targeted survey populations, but doesn’t. And it proved to be an earth-shaking failure in 1948 after three leading US pollsters—Gallup, Roper and Crossley—erroneously called the US presidential election in favor of Dewey instead of Truman. In the United Kingdom, where it persisted, it was blamed for the failure of the pollsters to predict Prime Minister John Majors’ victory in 1992.

“Quota sampling could never work in practice,” says Professor Warren. “Not only could pollsters not know the exact demographics so they could pick a representative sample that actually reflected the proper demographical proportions, but it was naïve to think that the interviewer could manage to interview the precise people needed to fill each quota.”

Thus today, reputable US pollsters rely almost exclusively on probability random sampling to create a “representative sample,” says Warren.

Why then do local pollsters continue to use quota sampling and face-to-face interviewing for their surveys? Why haven’t they adopted probability random sampling, which has protected US opinion polls from using contaminated data?

Of course, the same methodology is also still used in Eastern Europe, Africa and Latin America. But that is no excuse, given the high claim our local pollsters make for the supposedly advanced state of knowledge in their trade.

The situation would not have been so bad were the surveys meant simply and solely for the private consumption of clients. But as opinion polls have become a hot commodity and the stakes and rewards have gone up, pollsters have been led to make bigger and bigger claims for their products and thrown standards out the window.

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