Inferential Statistics

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

  1. Enter the sample mean (x̄): The average value from your sample
  2. Enter the standard deviation: Either population (σ) or sample (s) standard deviation
  3. Enter the sample size (n): Number of observations in your sample
  4. Select confidence level: Choose 90%, 95%, or 99%
  5. Select standard deviation type: Choose whether you’re using population or sample standard deviation
  6. 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:

CI=xˉ±(critical value)×σn\text{CI} = \bar{x} \pm (\text{critical value}) \times \frac{\sigma}{\sqrt{n}}

Where:

  • xˉ\bar{x} = sample mean
  • σ\sigma = standard deviation
  • nn = sample size
  • Critical value = zz or tt 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
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