Sorry, this page is no longer available
We may earn an affiliate commission when you visit our partners.

Confidence Intervals

Save
May 1, 2024 Updated May 9, 2025 19 minute read

A confidence interval is a range of values, derived from sample data, that is likely to contain an unknown population parameter. Instead of providing a single point estimate, such as an average, a confidence interval offers a range along with a specified confidence level, typically 95% or 99%. This means that if the same sampling procedure were repeated numerous times, the stated percentage of the resulting intervals would be expected to contain the true population parameter. For instance, if you construct a confidence interval with a 95% confidence level, you are confident that 95 out of 100 times the estimate will fall between the upper and lower values specified by the interval.

Path to Confidence Intervals

Take the first step.
We've curated 24 courses to help you on your path to Confidence Intervals. Use these to develop your skills, build background knowledge, and put what you learn to practice.
Sorted from most relevant to least relevant:

Share

Help others find this page about Confidence Intervals: by sharing it with your friends and followers:

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Confidence Intervals.
This advanced treatise delves deeply into the theory and applications of confidence intervals, offering a rigorous and comprehensive treatment of this fundamental statistical concept.
This comprehensive textbook covers both the theory and practice of confidence intervals in survey research, with updated content and new material reflecting recent developments in the field.
This comprehensive reference guide covers the design and analysis of confidence intervals in clinical trials, providing practical guidance for researchers in the medical field.
Is the most comprehensive and up-to-date treatment of confidence intervals for proportions and percentages.
This practical guide provides clear and concise instructions for constructing and interpreting confidence intervals in various statistical scenarios.
Uses a Bayesian perspective to explore confidence intervals and statistical inference, providing a different approach to understanding these concepts.
Concise and accessible introduction to confidence intervals, covering both the theory and practical applications.
Table of Contents
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser