Confidence Interval Calculator for Statistics

Calculate the confidence interval using your sample mean, standard deviation, and size. Select a confidence level for instant results, showing upper and lower limits. Suitable for researchers and statisticians.


Confidence Interval
Lower Bound
0
Upper Bound
0
Margin of Error
0

What is a Confidence Interval?

A confidence interval is a range of values that is likely to contain an unknown population parameter. It helps estimate the reliability of a sample statistic and is commonly used in research and data analysis.

How Does It Work?

The calculator uses the following formula: CI = x̄ ± (z × (s/√n)) Where: - x̄ is the sample mean - z is the z-score based on confidence level - s is the standard deviation - n is the sample size

Common Applications

Scientific Research

Estimating population parameters in experiments

Market Research

Understanding customer preferences and behaviors

Quality Control

Monitoring manufacturing processes

Medical Studies

Analyzing treatment effects and outcomes

Tips for Accurate Calculations

  • Use a large enough sample size (n ≥ 30 for normal distribution)
  • Ensure your data is normally distributed
  • Higher confidence levels mean wider intervals
  • Consider the practical significance of the interval width

Frequently Asked Questions

The confidence level (e.g., 95%) represents how confident you can be that the true population parameter falls within the calculated interval. A 95% confidence level means if you repeated the study 100 times, approximately 95 of those intervals would contain the true population value.

For reliable results, a sample size of at least 30 is recommended when your data follows a normal distribution. Smaller samples can still be used but may produce less reliable intervals. Larger samples generally result in narrower, more precise confidence intervals.

Wide confidence intervals can result from a small sample size, high variability (large standard deviation) in your data, or choosing a very high confidence level. To narrow your interval, consider increasing your sample size, which is the most effective approach.