Which of the following refers to an inaccurate representation caused by a biased sample?

The term that describes an inaccurate representation caused by a biased sample is sampling error. Sampling error occurs when a sample is not representative of the larger population, leading to misleading or incorrect conclusions about that population.

A biased sample can arise from various factors, such as the method of selection, the size of the sample, or the demographic characteristics of those selected. When the sample does not accurately reflect the diversity and characteristics of the entire population, the data gathered can lead to biased results.

In contrast, measurement error relates to inaccuracies in how data is collected or recorded, which would not be inherently related to the sample itself. Non-sampling error encompasses other issues in research that stem from factors outside of sampling, including design flaws and data processing mistakes. Qualitative data error typically refers to errors in handling non-numeric data, which may not directly link to sampling issues.

Understanding sampling error is crucial when evaluating research findings, as it highlights the importance of proper sampling techniques to ensure representative data collection.