# What does prediction interval mean

Contents

- 1 What does a 95% prediction interval mean?
- 2 What does the prediction interval tell us?
- 3 How do you describe a prediction interval?
- 4 How do you find the 95 prediction interval?
- 5 What’s the difference between a confidence interval and prediction interval?
- 6 How do you report a prediction interval?
- 7 What is prediction interval in meta analysis?
- 8 Why is the terminology of prediction interval used instead of confidence interval?
- 9 What does tolerance interval mean in statistics?

## What does a 95% prediction interval mean?

A prediction interval is a range of values that is likely to contain the value of a single new observation given specified settings of the predictors. For example, for a 95% prediction interval of [5 10], you can be 95%

**confident that the next new observation will fall within**this range.## What does the prediction interval tell us?

Prediction intervals tell

**you where you can expect to see the next data point sampled**. … Prediction intervals must account for both the uncertainty in estimating the population mean, plus the random variation of the individual values. So a prediction interval is always wider than a confidence interval.## How do you describe a prediction interval?

A prediction interval is a type of confidence interval (CI) used with predictions in regression analysis; it is

**a range of values that predicts the value of a new observation**, based on your existing model. … A prediction interval is where you expect a future value to fall.## How do you find the 95 prediction interval?

For example, assuming that the forecast errors are normally distributed, a 95% prediction interval for the h -step forecast is

**^yT+h|T±1.96^σh, y ^ T + h | T ± 1.96 σ ^ h**, where ^σh is an estimate of the standard deviation of the h -step forecast distribution.## What’s the difference between a confidence interval and prediction interval?

The prediction interval predicts in what

**range a future individual observation will fall**, while a confidence interval shows the likely range of values associated with some statistical parameter of the data, such as the population mean.## How do you report a prediction interval?

In addition to the quantile function, the prediction interval for any standard score can be calculated by (1 − (1 − Φ

_{µ}_{,}_{σ}^{2}(standard score))·2). For example, a standard score of x = 1.96 gives Φ_{µ}_{,}_{σ}^{2}(1.96) = 0.9750 corresponding to a prediction interval of (1 − (1 − 0.9750)·2) = 0.9500 = 95%.## What is prediction interval in meta analysis?

A prediction interval is defined as

**the interval within which the effect size of a new study would fall if this study was selected at random from the same population of the studies already**included in the meta-analysis.## Why is the terminology of prediction interval used instead of confidence interval?

Why is the terminology of prediction interval used instead of confidence interval? … The advantage of using a prediction interval is

**that it gives a range of likely weights**, so we have a sense of how accurate the predicted weight is likely to be.## What does tolerance interval mean in statistics?

The tolerance interval is

**a bound on an estimate of the proportion of data in a population**. A statistical tolerance interval [contains] a specified proportion of the units from the sampled population or process. … The range from x to y covers 95% of the data with a confidence of 99%.