Teaching the utilization of quantitative statistical techniques for industrial application: A case study.

John R. Gum; Prashant Kulkarni; Philip J. Trocchia

Teaching the utilization of quantitative statistical techniques for industrial application: A case study.

John R. Gum, Prashant Kulkarni, Philip J. Trocchia

University of South Florida

Research output: Contribution to journal › Article › peer-review

Abstract

This article describes a step-by-step sequence of statistical techniques, including linear regression and ANOVA, for use in a classroom setting in order to solve real-world problems encountered in business and industry. A powder coating operation is used as the context for the case study. The authors found that, by employing the quantitative techniques described, the optimal solution to the manufacturer’s powder coating problem was found in about a week, versus three years in the real-world industrial setting, using a nonstatistical trial-and-error process.

Original language	American English
Journal	Default journal
State	Published - Jan 1 2016

Keywords

Statistical analysis
Statistical techniques in manufacturing
Trial and error
Multiple linear regression
ANOVA

Disciplines

Business
Scholarship of Teaching and Learning

Access to Document

https://login.ezproxy.lib.usf.edu/login?url=http://search.proquest.com/docview/1874619731/fulltextPDF/97A25F7A7ABA454BPQ/6?accountid=14745

Cite this

@article{5ac35db9867b4e43b7de88b732e04732,

title = "Teaching the utilization of quantitative statistical techniques for industrial application: A case study.",

abstract = " This article describes a step-by-step sequence of statistical techniques, including linear regression and ANOVA, for use in a classroom setting in order to solve real-world problems encountered in business and industry. A powder coating operation is used as the context for the case study. The authors found that, by employing the quantitative techniques described, the optimal solution to the manufacturer{\textquoteright}s powder coating problem was found in about a week, versus three years in the real-world industrial setting, using a nonstatistical trial-and-error process.",

keywords = "Statistical analysis, Statistical techniques in manufacturing, Trial and error, Multiple linear regression, ANOVA",

author = "Gum, \{John R.\} and Prashant Kulkarni and Trocchia, \{Philip J.\}",

note = "Gum, J., Kulkarni, P., \& Trocchia, P. J. (2016). Teaching the utilization of quantitative statistical techniques for industrial application: A case study. Journal of the Academy of Business Education, 17 (2016), 52-61.",

year = "2016",

month = jan,

day = "1",

language = "American English",

journal = "Default journal",

}

TY - JOUR

T1 - Teaching the utilization of quantitative statistical techniques for industrial application: A case study.

AU - Gum, John R.

AU - Kulkarni, Prashant

AU - Trocchia, Philip J.

N1 - Gum, J., Kulkarni, P., & Trocchia, P. J. (2016). Teaching the utilization of quantitative statistical techniques for industrial application: A case study. Journal of the Academy of Business Education, 17 (2016), 52-61.

PY - 2016/1/1

Y1 - 2016/1/1

N2 - This article describes a step-by-step sequence of statistical techniques, including linear regression and ANOVA, for use in a classroom setting in order to solve real-world problems encountered in business and industry. A powder coating operation is used as the context for the case study. The authors found that, by employing the quantitative techniques described, the optimal solution to the manufacturer’s powder coating problem was found in about a week, versus three years in the real-world industrial setting, using a nonstatistical trial-and-error process.

AB - This article describes a step-by-step sequence of statistical techniques, including linear regression and ANOVA, for use in a classroom setting in order to solve real-world problems encountered in business and industry. A powder coating operation is used as the context for the case study. The authors found that, by employing the quantitative techniques described, the optimal solution to the manufacturer’s powder coating problem was found in about a week, versus three years in the real-world industrial setting, using a nonstatistical trial-and-error process.

KW - Statistical analysis

KW - Statistical techniques in manufacturing

KW - Trial and error

KW - Multiple linear regression

KW - ANOVA

UR - https://digitalcommons.usf.edu/fac_publications/2485

UR - https://login.ezproxy.lib.usf.edu/login?url=http://search.proquest.com/docview/1874619731/fulltextPDF/97A25F7A7ABA454BPQ/6?accountid=14745

M3 - Article

JO - Default journal

JF - Default journal

ER -

Teaching the utilization of quantitative statistical techniques for industrial application: A case study.

Abstract

Keywords

Disciplines

Access to Document

Other files and links

Cite this