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Full-Text Articles in Statistics and Probability

A Fortran List Processor (Flip), Karl A. Fugal May 1970

A Fortran List Processor (Flip), Karl A. Fugal

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A series of Basic Assembler Language subroutines were developed and made available to the FORTRAN IV language processor which makes list processing possible in a flexible and easily understood way.

The subroutine will create and maintain list structures in the computer's core storage. The subroutines are sufficiently general to permit FORTRAN programmers to tailor list processing routines to their own individual requirements. List structure sizes are limited only by the amount of core storage available.


A Report On The Statistical Properties Of The Coefficient Of Variation And Some Applications, Howard P. Irvin May 1970

A Report On The Statistical Properties Of The Coefficient Of Variation And Some Applications, Howard P. Irvin

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Examples from four disciplines were used to introduce the coefficient of variation which was considered to have considerable usage and application in solving Quality Control and Reliability problems.

The statistical properties were found in the statistical literature and are presented, namely, the mean and the variance of the coefficient of variation. The cumulative probability function was determined by two approximate methods and by using the noncentral t distribution. A graphical method to determine approximate confidence intervals and a method to determine if the coefficients of variation from two samples were significantly different from each other are also provided (with examples). …


Model For Bathtub-Shaped Hazard Rate: Monte Carlo Study, Glen S. Leithead May 1970

Model For Bathtub-Shaped Hazard Rate: Monte Carlo Study, Glen S. Leithead

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A new model developed for the entire bathtub-shaped hazard rate curve has been evaluated as to its usefulness as a method of reliability estimation. The model is of the form:

F(t) = 1 - exp - (ϴ1tL + ϴ2t + ϴ3tM)

where "L" and "M" were assumed known.

The estimate of reliability obtained from the new model was compared with the traditional restricted sample estimate for four different time intervals and was found to have less bias and variance for all time points.

This was a monte carlo study and the …