Google Data Analytics Professional Certification Practice Test

What is meant by "unbiased sampling"?

1. When every possible sample is taken

2. When a sample is representative of the population

3. When data is analyzed without errors

4. When data collection methods are varied

The correct answer is: When a sample is representative of the population

Unbiased sampling refers to the practice of selecting a sample that accurately reflects the characteristics of the larger population being studied. This means that the sample is representative of the population, allowing for valid conclusions and generalizations to be made from the sample data. When a sample is representative, it captures the diversity and variation within the population without favoring any particular group or outcome. This is crucial in statistics and data analysis to ensure that the findings are reliable and applicable to the broader context. The other options do not accurately depict what unbiased sampling entails. Taking every possible sample is related to complete enumeration rather than sampling. Analyzing data without errors refers to the accuracy and integrity of the analysis process, not the sampling method itself. Lastly, varying data collection methods can introduce bias if certain methods favor particular outcomes or demographics, rather than contributing to unbiased sampling.