When counting and measuring, what are two things to consider when taking a sample?

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When counting and measuring, the goal is to get a sample that accurately represents the whole population while gathering enough data to be confident in the results. Choosing an appropriate sample size and using random sampling are the two main ways to achieve that. A sensible range for the number of units to include—around 10 to 50 in many practical situations—strikes a balance between accuracy and effort. Too small a sample leads to more variability and unreliable estimates, while a larger sample improves precision but requires more work.

Random sampling means every unit in the population has an equal chance of being chosen, which helps prevent bias and ensures the sample reflects the full variety present. This is essential for counting and measuring because it makes the results more representative of the whole group. By contrast, focusing on characteristics like color or texture isn’t about how you select the sample, and the time of day can affect measurements in specific contexts but isn’t a fundamental requirement for obtaining a representative sample. Nonrandom sampling, on the other hand, tends to skew results because it over- or under-represents certain parts of the population.