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     Research Journal of Applied Sciences, Engineering and Technology


The use of Statistical Methods in Mechanical Engineering

Iram Saleem, Muhammad Aslam and Muhammad Azam
Department of Statistics, Forman Christian College University, Lahore 54000, Pakistan
Research Journal of Applied Sciences, Engineering and Technology  2013  7:2327-2331
http://dx.doi.org/10.19026/rjaset.5.4660  |  © The Author(s) 2013
Received: June 08, 2012  |  Accepted: July 18, 2012  |  Published: March 11, 2013

Abstract

Statistics is an important tool to handle the vast data of present era as statistics can interpret all the information in such a beauty that so many conclusions can be extracted from it. The aim of this study is to see the use of statistical methods in Mechanical Engineering (ME) therefore; we selected research papers published in 2010 from the well reputed journals in ME under Taylor and Francis Company LTD. More than 350 research papers were downloaded from well reputed ME journals such as Inverse Problem in Science and Engineering (IPSE), Machining Science and Technology (MST), Materials and Manufacturing Processes (MMP), Particulate Science and Technology (PST) and Research in Nondestructive Evaluation (RNE). We recorded the statistical techniques/methods used in each research paper. In this study, we presented frequency distribution of descriptive statistics and advance level statistical methods used in five of the ME journals in 2010.

Keywords:

Descriptive statistics, mechanical engineering, statistical methods,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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