JOINT DISTRIBUTION OF X(BAR) AND X SUB (N) FOR A RANDOM SAMPLE FROM THE STANDARD NORMAL DISTRIBUTION WITH APPLICATIONS TO A VARIABLES SAMPLING INSPECTION PROCEDURE WHICH GUARANTEES ACCEPTANCE OF PERFECTLY SCREENED LOTS

Abstract

Tables of the joint distribution of the sample mean and the largest observation in a sample for a random sample from the standard normal distribution are presented for a variables sampling inspection procedure which guarantees acceptance of perfectly screened lots. The quality of each item in the lot is described by a single quality characteristic. It is assumed that this quality characteristic has a normal density function with known variance. Tables of standard truncated normal distribution required to compute the tables of the joint distribution of X(Bar) and X sub (n) are also presented. The two sets of tables are also used to show how operating characteristic curves may be computed. Sample size is shown to affect the existence of levels of significance. For small sample sizes certain large levels of significance do not exist for tests of hypothesis concerning truncated normal distributions.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1964
Accession Number
AD0481330

Entities

People

  • Jerome D. Julius

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Data Science
  • Distribution Functions
  • Guarantees
  • Information Science
  • Inspection
  • Normal Density Functions
  • Normal Distribution
  • Observation
  • Probability
  • Probability Distributions
  • Random Variables
  • Sampling
  • Standards
  • Statistical Samples
  • Statistics
  • United States

Fields of Study

  • Mathematics

Readers

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  • Psychometric Testing or Psychological Assessment.
  • Structural Health Monitoring of Composite Structures.