Research Topics:

Data Analysis | Quantitative Research

Content Type:

Glossary

Confidence Interval Definition

The range around a survey result for which there is a high statistical probability that it contains the true population parameter.

A confidence interval is a statistical range in which there is high probability that survey results contain the true population parameter. It measures the uncertainty with sample estimates and provides a range where the true population parameter probably will fall. A narrow confidence Interval suggests higher precision, while a wider interval indicates greater uncertainty. This measurement usually is represented as a percentage. Confidence intervals provide data for marketing research for several reasons, including making decisions, interpreting research results, comparing data and subsets within a study, planning sample size and communicating with stakeholders. 

Who relies on confidence intervals?

Marketing researchers, analysts and decision makers rely on confidence intervals to judge the reliability and precision of research findings. They provide evidence of the potential variability in the population parameter in which they are studying. By having a range of potential values, marketing professionals can judge the accuracy of their conclusions and the level of uncertainty associated with their results.

Why should I care about confidence intervals?

Confidence intervals offer insights into the reliability of the data and the potential variability of the results. An understanding of confidence intervals allows marketing professionals to gauge the level of certainty associated with their findings. The intervals provide insights that can lead to better decision-making and forecasts. The insights aid in making more informed marketing decisions and setting realistic expectations.