Title: Statistical analysis of iron concentrate quality data

Authors: Xiaomin Xu; Kewei Wu

Addresses: School of Business, Shanghai Dianji University, No. 300, Shuihua Road, Lingang New Town, Pudong New District, 201306, Shanghai, China ' School of Medicine, Shanghai Jiaotong University, No. 227, South Chongqing Road, Huangpu District, 200025, Shanghai, China

Abstract: China's steel industry is gradually converging with the international one and is becoming an important force in the international steel industry. However, there exists a big gap between the quality of China's iron concentrate and the world standard. This paper takes the iron concentrate of a mining company as the object of quality analysis and improvement. Firstly, the toxic element sulphur in iron concentrate was found, which affects the quality of smelting steel. Secondly, the multiple linear regression method was used to analyse the indexes of influencing factors, in order to find out the key factors affecting the sulphur content. Finally, the effect of sulphur content in iron concentrate was verified by a hypothesis test, and improved results were achieved.

Keywords: data of iron concentrate; statistical analysis; quality analysis; quality improvement; software analysis; multiple regression analysis; hypothesis testing.

DOI: 10.1504/IJDS.2022.126857

International Journal of Data Science, 2022 Vol.7 No.2, pp.181 - 196

Received: 18 Feb 2022
Received in revised form: 25 May 2022
Accepted: 02 Jun 2022
Published online: 09 Nov 2022 *

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