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Reseach Article

A Soft-Drink Experiment using Replicated Full Factorial (RFF) Design

by Arfa Maqsood, Rafia Shafi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 171 - Number 1
Year of Publication: 2017
Authors: Arfa Maqsood, Rafia Shafi
10.5120/ijca2017914957

Arfa Maqsood, Rafia Shafi . A Soft-Drink Experiment using Replicated Full Factorial (RFF) Design. International Journal of Computer Applications. 171, 1 ( Aug 2017), 25-30. DOI=10.5120/ijca2017914957

@article{ 10.5120/ijca2017914957,
author = { Arfa Maqsood, Rafia Shafi },
title = { A Soft-Drink Experiment using Replicated Full Factorial (RFF) Design },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2017 },
volume = { 171 },
number = { 1 },
month = { Aug },
year = { 2017 },
issn = { 0975-8887 },
pages = { 25-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume171/number1/28147-2017914957/ },
doi = { 10.5120/ijca2017914957 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:18:17.555003+05:30
%A Arfa Maqsood
%A Rafia Shafi
%T A Soft-Drink Experiment using Replicated Full Factorial (RFF) Design
%J International Journal of Computer Applications
%@ 0975-8887
%V 171
%N 1
%P 25-30
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An experiment using factorial design allows one to examine simultaneously the effects of multi-independent factors and their degree of interactions. In this paper, a replicated full-factorial (RFF) design is run to determine the factors that have significant impact on the response of soft drink experiment. We consider the four factors each with two levels and observe the impact of these factors on the volume of foam of soft drink when pour into a glass. Our investigation finds that the significant main effects are soft drink type (A), amount of soft drink (C), and diameter of glass (D), whereas the significant two-factor interactions B (temperature) with C, and C with D. Furthermore, to support our analysis we do modeling using regression approach based on significant factors and interactions. From the analysis of model adequacy, it is observed that the assumptions underlying the estimated model are appropriate.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Replicated full-factorial design Soft drink Interactions Regression analysis Model adequacy