Confidence Intervals for the Mean in Selecting an Appropriate Time-Dependent Distribution Model for Processes with Non-Normal Instantaneous Distributions
Abstract
Purpose: This paper proposes using confidence intervals for the mean to select
a suitable time-dependent distribution model for a process with non-normal instantaneous distributions.
Methodology/Approach: The approach examines a studied characteristic by analysing its distribution, location, dispersion, and shape, all of which are time functions. The values of the characteristic are determined by sampling from the process flow. A time-dependent distribution model represents the process.
Findings: The paper explains how to utilise confidence intervals for the mean when selecting an appropriate time-dependent distribution model for processes with non-normal instantaneous distributions.
Research Limitation/Implication: The methods described in this document pertain exclusively to continuous quality characteristics and can be applied to analyse processes across various industrial and economic sectors. The presented procedures are appropriate for use when the instantaneous distributions are non-normal.
Originality/Value of paper: Confidence intervals for the mean can improve decision-making when selecting a suitable time-dependent distribution model.
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