# Confidence interval Vs Prediction interval

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• #31116

Ravishankar
Participant

Hi,
Can anyone please explain what is the differnce between Confidence interval & Prediction interval. I know this much that the former is used for parameters distrinution and the later for future outcomes.

Regards,
Ravishankar S

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#81812

abasu
Participant

Confidence interval is an estimate for population mean (Xbar) whereas prediction interval is for future outcome of an individual value (Xi)

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#81827

John Dubuc
Participant

For completeness, there are three general types of Interval Estimates: Confidence Intervals, Prediction Intervals, and Tolerance Intervals. Each has associated subtypes for special applications. All three intervals estimate unknowns with a specified (1-alpha) degree of confidence.

Confidence Intervals estimate population parameters, and are generally meaningful to the producers of a product.

Prediction Intervals estimate the future value of a single observation (or small number of observations) from a population, and are of interest to the consumers of a product.

Tolerance Intervals estimate a specified proportion of the population. For example we can be 95% confident that at least p% of the population is captured by the sample interval. These estimates are useful in situations where process tolerance limits (specs) are determined by process variability such as in tolerance design.

Its important to remember that the confidence level associated with any of these intervals refers to the procedure used to construct the interval and not the particular interval you calculate from the sample.

Warmest regards

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#81932

Guest
Participant

Why are these intervals inportant? How do you use them?

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#81997

John Dubuc
Participant

Here’s a link to get you started using and interpreting statistical intervals:
http://www.itl.nist.gov/div898/handbook/index.htm

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#82956

John Turner
Participant

I think an important distinction between the two types of intervals is that prediction intervals refer to observable quantities, such as future observations. Confidence intervals refer to parameters, such as probability, that cannot be observed, but still describe the process.
If we wish to describe the mean of a distribution, we would use a confidence interval. If we want to put a bound on the next observation from the distribution, we would use a prediction interval.

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#130287

tclimb
Member

excellent responses. huge help. thanks!

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#130298

Participant

Mr Turner .,
sir,Can u be contacted through mail?if so mail id please .
thanks & regards .,
gsd

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#130305

Ken Feldman
Participant

By any chance did you happen to notice the date of the post?  It is 2 years old!!!!!!

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