When Should I Use Confidence, Prediction, and Tolerance Intervals?

Among the many data analysis methods that are handled while designing for the development of masterpiece goods or performing quality control and production management activities, there are methods that are expressed as interval values.
Typical interval statistic values include what are called confidence intervals, prediction intervals, and tolerance intervals.
A confidence interval is a range obtained from a sample statistic that is likely to include a parameter of an unknown population, such as the mean, standard deviation, and so on.
The prediction interval is a range that expresses the possibility of including the response value of a new observation when the predictor variable settings of the model are specified and a new production is made with those settings.
And, the tolerance interval is the range that is likely to contain the specified population proportion.
Today, I will introduce the meaning and characteristics of these statistical interval values.
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