Google Data Analytics Professional Certification Practice Test

What term describes the probability that a sample size accurately reflects the larger population?

1. Confidence interval

2. Confidence level

3. Significance level

4. Sampling error

The correct answer is: Confidence level

The term that describes the probability that a sample size accurately reflects the larger population is known as the confidence level. The confidence level indicates the degree of certainty that the population parameter falls within a specified range, represented by the confidence interval. For instance, if a study reports a 95% confidence level, this suggests that if the same sampling method were used repeatedly, approximately 95% of the calculated confidence intervals would contain the true population parameter. This concept is crucial in statistics, as it helps researchers to understand the reliability and validity of their sample-based estimates. A higher confidence level implies greater assurance regarding the sample's representativity of the overall population, which is vital for making informed decisions based on the data analyzed. While terms like confidence interval and significance level are related to understanding data around population parameters, they serve different purposes. The confidence interval indicates the range of values around the sample statistic, while the significance level is mainly used in hypothesis testing to determine if the results are statistically significant. Sampling error, on the other hand, refers to the difference between the sample statistic and the actual population parameter, but it does not describe the probability aspect of how accurately the sample reflects the population.