Confidence level refers to the degree of certainty that a statistical result or estimate is accurate. It is often expressed as a percentage, indicating how often the true value would fall within a specified range if the same study were repeated multiple times. For example, a 95% confidence level suggests that if the experiment were conducted 100 times, the true value would lie within the estimated range 95 times. In research and data analysis, confidence levels help determine the reliability of results. Higher confidence levels indicate greater certainty, while lower levels suggest more variability. This concept is crucial in fields like statistics, science, and market research to make informed decisions based on data.