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Why we need to designing experiment?

** Answer this question, please include your name, matric number and the reference

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Investigators perform experiments in virtually all fields of inquiry, usually to discover
something about a particular process or system or to confirm previous experience or theory. (Book-2017:

Design and Analysis of Experiments

By Douglas C. Montgomery)

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We need to designing experiment so that the variability in the experiment or the subject we wish to study can be contol and to reduce the amount of experimental errors  in order to improve the significance of the result from the experiment.
(Statistics Glossary v1.1: Valerie J. Easton and John H. McColl's)

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We need to designing experiment to investigate the effects in output of the process with the control variations of input of the process. With the obtained result, we can make analysis that allow to characterize, optimize and discover faults of the process.
(PDF DESIGN OF EXPERIMENTS: ITS IMPORTANCE IN THE EFFICIENT PROJECT MANAGEMENT by J.P.E. Souza, J.M. Alves, J.H.S. Damiani, M.B. Silva)

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Design analysis and experiment is determine the relationship between factors affecting a process and the output of that process. In other words, it is used to find cause-and-effect relationships. This information is needed to manage process inputs in order to optimize the output.

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By designing experiment can minimize any bias in the comparison of the result so that the error is small. Moreover, it also allows the experimenter to make stronger inferences about the nature of differences that can see in the experiment.
(EBook-2010: First Course in Design and Analysis of Experiments By Gary W. Oehlert)

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When we design experiment means we will deal with planning, conducting, analyzing, and interpreting controlled tests to evaluate the factors that control the value of a parameter or group of parameters.  The reasons why we need to designing experiment is because when we want to determine the relationship between factors affecting a process of our experiment and the output of that process. In other words, it is used to find cause-and-effect relationships.

DESIGN OF EXPERIMENTS – A PRIMER

By K.Sundararajan

https://www.isixsigma.com/tools-templates/design-of-experiments-doe/design-experiments-%E2%90%93-primer/

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Why we need to designing the experiment is that we can control the variability and closer conformance to nominal or target requirements. Besides that, by designing the experiment also can improved the process yield.
(EBook-2013: Design and Analysis of Experiments Eighth Edition By Douglas C. Montgomery)

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Tengku Nurul Aimi Balqis binti Tengku Malim Busu (255657)

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Tengku Nurul Aimi Balqis binti Tengku Malim Busu (255657)

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Weo need to design experiment because to improve the significance of an experimental result, replication, the repetition of an experiment on a large group of subjects, is required. If a treatment is truly effective, the long-term averaging effect of replication will reflect its experimental worth.

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we need experimental designing to increase the importance of an experimental result, some more to control variability so that treatment effect can be identified.

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Designing an experiment allows us to have more conditions to be measured and the more tightly controlled the variation between conditions is, the more reliably we can talk about situations in general and about the causes and influences of behavior.
(Book-2011:
Experimental Design: From User Studies to Psychophysics
By Douglas W. Cunningham)

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In real world, there are many uncertainties and variability that affecting a subject of study. In such, it is important to control the variability so that the appropriate treatment effects can be identified. That's why experimental design comes from. In the process of designing experiment, different factors are controlled at different levels according to the suitable experimental design method as to test for the outcome and the responses should be recorded down. In my opinion, the experimental design is very significant to curb with the real world problems such as medical and industrial fields to determine the best or the most appropriate treatments available. in fact, different objects of study such as human being tend to give a different (non - identical) responses that's why experimental design exists. In short,  Design of Experiments - DoE is a method that allows studying effects on process outputs with controlled variation of input variables.

Source:
1. George E. P. Box, William G. Hunter and J. Stuart Hunter, Statistics for Experimenters - An Introduction to Design, Data Analysis, and Model Building (John Wiley and Sons, Inc. 1978).

2. Souza, J.P.E.; Alves, J.M.; Damiani, J.H.S.; Silva, M.B. (2013). Design of Experiments: Its Importance In The Efficient Project Management. International Conference on Production Research.

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SITI ZUHAIRAH BINTI ABDUL RAHMAN (254566)

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SITI ZUHAIRAH BINTI ABDUL RAHMAN (254566)

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We need to design an experiment is because to allow estimates to be made of the sensitivity to variations in the several factors. This can help decide whether any of the variations seen are of practical importance. A good design also allows these estimates of sensitivity to be made against an error background that is reduced compared to the actual error. This is accomplished by causing the effects of the factors to be effectively “averaged,” thus reducing the effect of error by the square root of the number of items being averaged.

Next, we can also optimize some characteristic of the experimental system through designing an experiment.

Lastly, designing an experiment can Increase efficiency of resource use, that is, obtain the desired information using the fewest possible necessary experiments (this is usually what is thought of when “statistical experimental designs” are considered). This aspect of experimentation is particularly important when the experiment is large to begin with, or if the experiment uses resources that are rare or expensive, or if the experiment is destructive so that materials (especially expensive ones) are used up.

SOURCE: Howard Mark, Jerry WorkmanJr., in Chemometrics in Spectroscopy (Second Edition), 2018

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We need to design experiment  because   to more understanding how process and product parameters affect response variables such as processability, physical properties, or product performance. It is a tool similar to any other tool, device, or procedure that makes the job easier.  It uses statistical methodology to analyze data and predict product property performance under all possible conditions.
(Book-2014 :
Extrusion (Second Edition)
By John R. Wagner, Jr., Eldridge M. Mount, III and Harold F. Giles, Jr.)

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Before conducting the experiment, the particular questions to be answered must be obviously recognized. In experimental units, we should also try to identify known or expected sources of variability because one of the primary purposes of a designed experiment is to reduce the impact on answers to questions of interest from the sources of variability. That is, to enhance the accuracy of our responses, we design the experiment.

Source :
Statistics Glossary v1.1 :  Valerie J. Easton and John H. McColl's

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Designing experiment is when the questions that the experiment intended to  answer need to be clearly identified before carrying out the experiment. The purposed of we need to designing experiment is because of the variability in the experimental units since the main aim is to reduce the effect of the variability of the sources on the questions. That it, we designing the experiment  in order to improve the precision of the answers.

SOURCE :
Valerie J. Easton and John H. McColl's Statistics Glossary v1.1

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Designing experiment is a systematic approach to understanding how process and product parameters affect response variables such as processability, physical properties, or product performance. It is a tool similar to any other tool, device, or procedure that makes the job easier. In addition to understanding how a particular variable affects product performance, interactions between different process and product variables are identified.

SOURCE :

John R. WagnerJr., ... Harold F. GilesJr., in Extrusion (Second Edition), 2014

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The analysis of a complex process requires the identification of target quality attributes that characterize the output of the process and of factors that may be related to those attributes. Once a list of potential factors is identified from subject‐matter expertise, the strengths of the associations between those factors and the target attributes need to be quantified. A naïve, one‐factor‐at‐a‐time analysis would require many more trials than necessary. Additionally, it would not yield information about whether the relationship between a factor and the target depends on the values of other factors(commonly referred to as interaction effects between factors)

Design and Analysis of Experiments by Douglas Montgomery: A Supplement for Using JMP(R)

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What is the difference between  analysis of fixed & random effects model?