Confidence Interval Calculator
Calculate confidence intervals for population means with this free calculator. Get step-by-step explanations and interpretations.
Confidence Interval Calculator
Calculate confidence intervals for a population mean using either the z-distribution (when population standard deviation is known) or the t-distribution (when using sample standard deviation).
How to Use This Calculator
- Enter the sample mean (x̄): The average value from your sample
- Enter the standard deviation: Either population (σ) or sample (s) standard deviation
- Enter the sample size (n): Number of observations in your sample
- Select confidence level: Choose 90%, 95%, or 99%
- Select standard deviation type: Choose whether you’re using population or sample standard deviation
- Click Calculate: Get your confidence interval with full explanation
Understanding Confidence Intervals
A confidence interval provides a range of plausible values for an unknown population parameter. Instead of a single point estimate, you get:
- Lower bound: The lowest plausible value
- Upper bound: The highest plausible value
- Margin of error: How much uncertainty exists in your estimate
- Confidence level: The probability that your method captures the true parameter
Example Interpretation
If a 95% confidence interval for average height is (165 cm, 175 cm):
✅ Correct: “We are 95% confident that the true population mean height is between 165 cm and 175 cm.”
❌ Incorrect: “There is a 95% probability that the mean is in this interval.” (The parameter is fixed, not random!)
When to Use z vs t Distribution
Use z-distribution when:
- Population standard deviation (σ) is known
- Any sample size
Use t-distribution when:
- Population standard deviation is unknown (using sample s)
- Especially important for small samples (n < 30)
- As sample size increases, t-distribution approaches z-distribution
Formula
The general form of a confidence interval for a mean is:
Where:
- = sample mean
- = standard deviation
- = sample size
- Critical value = or value depending on the situation
Factors Affecting Interval Width
Three factors influence how wide your confidence interval is:
1. Confidence Level
- Higher confidence → Wider interval
- 99% CI is wider than 95% CI
2. Sample Size
- Larger sample → Narrower interval
- Standard error decreases as √n increases
3. Variability
- More spread in data → Wider interval
- Higher standard deviation = more uncertainty
Common Applications
- Clinical trials: Estimate treatment effects
- Quality control: Monitor production processes
- Market research: Estimate customer satisfaction scores
- Education: Assess average test performance
- Finance: Estimate average returns
Related Resources
- Confidence Intervals Lesson - Learn the theory
- T-Test Calculator - Compare means
- Sample Size Calculator - Plan your study
Want to learn the theory?
Our lessons explain the statistical concepts behind this calculator with clear examples.
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