Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-23T12:51:57.413Z Has data issue: false hasContentIssue false
  • English
  • Français

Applications of Computerized Statistical Techniques in Quantitative X-Ray Analysis

Published online by Cambridge University Press:  06 March 2019

Betty J. Mitchell
Betty J. Mitchell*
Affiliation:
Chemicals and Plastics Division Union Carbide Corporation Charleston, West Virginia
Get access

Abstract

The place of statistical techniques and the digital computer in analytical chemistry is clearly exemplified in the X-ray spectrograph laboratory. As the statistician is obsolete who uses only a desk calculator for his calculations in this era of rapidly changing technology and the need for increased productivity, so the X-ray man is severely handicapped who ignores the place of statistical techniques and associated digital computation in his work. For his calculations, the statistical X-ray analyst may choose from among the following: a small specialized computer designed as part of his X-ray equipment, a medium-size computer located in the laboratory building with the capacity to handle all the problems generated by the various analytical specialists, a time-sharing computer station which he shares with other analytical or testing sections of his main laboratory, or batch processing of his data by his company's computer center. Advanced types of desk calculators are now available which will permit rapid completion of some types of complex calculations, especially if they are set up in a systematic fashion. Careful study of an individual laboratory's problems will provide economic justification for the most appropriate type of computer calculation; the choice is dependent on many factors. This paper describes the advantages and disadvantages of the various computer systems for the X-ray spectrographer and the numerous statistical techniques which he may employ as an aid in hi? work. Statistics provide him with the tools to design his experiments, interpret his data, control the process which supplies his samples, improve sampling procedures, calibrate his X-ray equipment, perform theoretical studies, and calculate, correct, average, and evaluate his analyses. Digital computation provides him with an extraordinarily rapid means of making these calculations; in some cases, they are virtually impossible without computerization. Examples of analyses are described which are made practicable only by this combined statistical computerized approach. The accuracy and precision of computerized analyses are higher than for results obtained by the usual X-ray methods; analyst error is reduced to a minimum. The economics of present-day industrial life, especially applied to the analytical laboratory as a service organization, demand the most efficient possible operation of all analytical equipment. The X-ray laboratory presents an outstanding example of the need for statistical analysis and its associated digital-computer computation.

Type
Research Article
Information
Advances in X-Ray Analysis , Volume 11: Sixteenth Annual Conference on Applications of X-ray Analysis, August 9-11, 1967 , 1967 , pp. 129 - 149
Copyright
Copyright © International Centre for Diffraction Data 1967

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Slonim, M. J., “Sampling in a Nutshell,” Am. Statistical Assoc. J., 52: 143, June 1957.Google Scholar
2. Savitzky, A., “Computers Reduce Data for Better Quality Control,” Chem. Eng. 73: 99, 1966.Google Scholar
3. Bennett, C. A. and Franklin, N. L., Statistical Analysis in Chemistry and the Chemical Industry, John Wiley & Sons, Inc., New York, 1954.Google Scholar
4. Davies, Owen L., The Design and Analysis of Industrial Experiments, Hafner Publishing Co., New York, 1954.Google Scholar
5. Anderson, R. L. and Bancroft, T. A., Statistical Theory in Research, McGraw-Hill Book Company, New York, 1952.Google Scholar
6. Brownlee, K. A., Statistical Theory and Methodology in Science and Engineering, John Wiley & Sons, Inc., New York, 1960.Google Scholar
7. Dixon, W. J. and Massey, F. J., Introduction to Statistical Analysis, McGraw-Hill Book Company, New York, 1951.Google Scholar
8. Fisher, R. A., The Design of Experiments, Hafner Publishing Co., New York, 1960.Google Scholar
9. Natrella, M. G., “Experimental Statistics,” Natl. Bur. Std. (U.S.) Handbook 91, 1963.Google Scholar
10. Matthias, R. H., “Use of Subsampling in Control Laboratory Problems,” Anal. Chem. 29: 1046, 1957.Google Scholar
11. Bainbridge, T. R., “Staggered, Nested Designs for Estimating Variance Components,” Industrial Quality Control, p. 12, July 1965.Google Scholar
12. Hopper, F. N., “Notes for Instruction in Statistical Control,” Unpublished manuscript, Union Carbide Corp., 1962.Google Scholar
13. Duncan, A. J., “Quality Control and Industrial Statistics,” Richard D. Irwin, Inc., Homewood, Illinois, 1953.Google Scholar
14. Mitchell, B. J. and Hopper, F. N., “Digital Computer Calculation and Correction of Matrix Effects in X-Ray Spectroscopy,” Appl. Spectry. 20: 172, 1966.Google Scholar
15. Andermann, G. and Kemp, J. W., “Scattered X-Rays as Internal Standards in X-Ray Emission Spectroscopy,” Anal. Chem. 30: 1306, 1958.Google Scholar
16. Traill, R. J. and Lachance, G. R., “A New Approach to X-Ray Spectra chemical Analysis,” Can. Dept. Mines Tech. Sum. Geol. Surv. Can., Paper 64-57, 1965.Google Scholar
17. Shiraiwa, T., “Application of Theoretical Calculations to X-Ray Fluorescent Analysis,” in: Pittsburg Conf. on Anal. Chemistry and Applied Spectroscopy, Paper No. 284, March 1967.Google Scholar
18. Mitchell, B. J., “A Study of the Complete Pattern of Calibration Curves for a Variety of Matrices,” 12th Annual Symposium on Spectroscopy, Chicago, Illinois, May 1961.Google Scholar