Statistical approaches in surface finishing.: Part 1. Introductory review and parametric hypothesis testing

James Smith; C. Larson

doi:10.1080/00202967.2016.1232851

Statistical approaches in surface finishing. Part 1. Introductory review and parametric hypothesis testing

James Smith, C. Larson

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Abstract

This paper is the first of a short series of articles aimed towards describing some of the various statistical methods and approaches that have been used in surface finishing. The methods fall broadly into two areas: analysis and design-of-experiments. This article introduces the subject, briefly reviewing the wide use of a number of experimental design tools in recent surface finishing research before starting with a discussion of parametric hypothesis testing, the simplest of the statistical methods.

Original language	English
Pages (from-to)	288-293
Journal	Transactions of the Institute of Metal Finishing
Volume	94
Issue number	6
Early online date	9 Nov 2016
DOIs	https://doi.org/10.1080/00202967.2016.1232851
Publication status	Published - Dec 2016

Keywords

Statistics
Frequency distribution
Parametric
Normality
Heterogeneity
Variance
Student’s t-test
ANOVA

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10.1080/00202967.2016.1232851

TIMF_Stats_Pure
This is an Accepted Manuscript of an article published by Taylor & Francis in Transactions of the Institute of Metal Finishing on 09/11/2016, available online: http://dx.doi.org/10.1080/00202967.2016.1232851
Accepted author manuscript (Post-print), 1.36 MB

5 Citations
1 Article

Statistical approaches in surface finishing. Part 2. Non-parametric methods for data analysis
Smith, J. & Larson, C., Jan 2019, In: Transactions of the Institute of Metal Finishing. 97, 1, p. 5-10 5 p.
Research output: Contribution to journal › Article › peer-review

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Cite this

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KW - Normality

KW - Heterogeneity

KW - Variance

KW - Student’s t-test

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Statistical approaches in surface finishing. Part 1. Introductory review and parametric hypothesis testing

Abstract

Keywords

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Research output

Statistical approaches in surface finishing. Part 2. Non-parametric methods for data analysis

Cite this