How to Minimize Bias in Sampling Oranges from a Truckload

When conducting a convenience sample of oranges from a truckload, several types of bias can occur. The most relevant types of bias in this scenario are under-coverage bias, selection bias, and potentially response bias.

Under-coverage bias happens because the sample may not represent all segments of the population of oranges in the truck; for example, if the oranges at the top are more accessible and thus more likely to be chosen, they may not reflect the quality or variety of the oranges deeper in the load. Selection bias is present since the oranges are not randomly selected and thus may not be representative. While response bias often refers to human survey responses, it could metaphorically apply to oranges if, for example, the oranges 'responded' differently to being selected due to their exposure or position in the truck, although this is less typical in the context of sampling objects.

The types of bias that are less relevant or not applicable in this scenario are respondent bias, question wording bias, non-response bias, and interviewer bias, since they typically apply to human subjects and surveys rather than to the sampling of inanimate objects like oranges.