Why do we need Sampling?

Sampling is used when we try to draw a conclusion without knowing the population. Population refers to the complete collection of observations we want to study, and a sample is a subset of the target population. Here’s an example. A Gallup poll¹, conducted between July 15 to 31 last year, found that 42% of Americans approve of the way Donald Trump is handling his job as president. The results were based on telephone interviews of a random sample of ~4500 calls (assuming one adult per call. ~4500 adults), aged 18 and older, living in the U.S. The poll was conducted during a period of controversy over Trump’s social media comments. For this survey, the population is ALL the U.S citizens aged 18 and older, and the sample is 4500 adults.

If sampling is done wrong, it will lead to biases that affect the accuracy of your research/survey results. To avoid selection biases, we have to carefully choose a subset of a populationthat can be representative of the group as a whole.

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