I draw 20 Experiments with 3 factors for Optimization. I'm using Central Composite Design. So how we can analyze data, statistical analysis and make 3d graph? And How we know our data is significant ?
Dear Hamza Armghan Noushahi
To analyze the data, you have to look at several important factors including ANOVA which have many important parameters including:
P value: when P 4 is desired)
Coefficient of variance CV: indicate the reproducibility of the model can be measured as the percent ratio of the standard error of the estimate to the mean value of the response. A value of less than 10% indicates that the model can be considered reproducible.
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You can look for the 3D graph tap and select the paramters you want to exhibit and export the graphs.
You can also read our article (attached) in which we used CCD design for 3 factors to investigate the biosorption removal of heavy metals onto red algae
Stay safe and good luck!
Mubeen Isam
How i wish to take you through the journey of experimental design using response surface methodology but its not something I can texplain everything here but I will help you by attaching a handout I wrote specifically for people like you who which to analyse CCD design using design expert. Kindly find the attachment below. Kindly go through the handout, you will find it useful.
Normally, three main tests, including (1) significant of terms, (2) regression model and (3) lack-of-fit test is used to assess the fitness and reliability of the model.
1- Significant of terms can be evaluates based on P-value, lower P-value (typically less than 0.05) suggests the significance of the model and model terms. Otherwise, model or model terms with P-value exceed 0.05 consider insignificant and hence will not be involved in the final equation.
2- The significant model should have insignificant lack-of-fit (P-value higher than 0.05).
3- A good model should also have R-squared close to 1 (equal or higher than 0.9). That means good fitness between experimental and predicted values.
4- The reproducibility of the model can be assessed using coff. of Var. (CV) and Pred. Errors Sum of Squared (PRESS). Normally, CV (equal or less than 10%) and PRESS (higher than 4) consider acceptable.
To gain a better understanding, you can follow our article in which we explained in detail the evaluation process of faced-centered CCD for optimizing the synthesis of carbon dots.
Article Fabrication, characterization and response surface method op...
Mohammed Abdullah Issa Thank you for your guidance i really appreciate. I want to ask one thing.. what if your lake of fitness test is also significant? And how I can adjust it?
Please check your direct messages, I just sent you video and slides on the way of obtaining insignificant LOF. Hope it is useful.
Regards.
Mohammed Abdullah Issa can you send those slides and video to me as well?
Mohammed Abdullah Issa can u please send me the videos and slides for data analysis of RSM
Thanks
I have provided the links to the lecture series on how to apply RSM (CCD) through a design expert. In these tutorials, everything is explained. Hopefully, it will solve your all problems from research designing to writing research articles.
RSM experimental design: https://youtu.be/QWWgL3no9a0
RSM data analysis: https://youtu.be/Nyh-Ba_j8l4
RSM optimization: https://youtu.be/CjnNzv8HlQs
RSM Tables for Research Article: https://youtu.be/uM2uRYcWrbM
RSM Tables for Research Article: https://youtu.be/2SKusIIBE6I
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
I’m also want to learn RSM, please help me, i’m from UniSZA, Terengganu. Thanks
please find attachment this review paper explain response surface methodology in detailed @ Hamza Noushahi
Chapter Utilization of Response Surface Methodology in Optimization ...
You can find the details in attached paper. Basically, the experimental data are evaluated to fit a statistical model (Linear, Quadratic, Cubic or 2FI (two factor interaction)). The coefficients of the model are represented by constant term, A, B and C (linear coefficients for independent variables), AB, AC and BC (interactive term coefficient), A2, B2 and C2 (quadratic term coefficient). Correlation coefficient (R2), adjusted determination coefficient (Adj-R2) and adequate precision are used to check the model adequacies; the model is adequate when its P value < 0.05, lack of fit P value > 0.05, R2 > 0.9 and Adeq Precision >4.
And more importantly, you have to check if your model's p value is lower than 0.05 and lack of fit p value is higher than 0.05 then you can say that model is well fitted to your data
You can also see the following article. same set of experiment has been conducted.
Article Enhancement of Laser Transmission Welds in Acrylic and Polyp...
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