Hi Teaching Junction - I really appreciate your effort of putting an example that helps explain the basics of the software. Please let me know if I can connect with you over linked-in or email. I have some questions on design of experiments, or if I can hire someone who can do that for me. Looking forward to it. Thanks once again.
Thank you for your explanation but I have a question I didn't understand when we first enter the rsponses to do the analysis are those rsponse already predicted as u said after the optimization done we need to perform another experiment to see the difference between predicted and actual response ?? bit confuse 😢😢 and I NEED HELP
The model predict response after optimization step. After optimization RSM predict optimized level of independent variable as well as potential response
@@TeachingJunction Thank you so much😇❤️ I'm following ur design expert to learn it very well explained plz make more detail videos if possible about the each analysis. Then the predicted response after optimization should be very close to what we enter the actual response when we did the experiment but what if it's not?? should we again start from the beginning
You can make 3D graph by keeping in mind the independent variables. If you have 3 independent variables (A, B and C), you can make two 3D graphs of AB and BC for individual response. The purpose of 3D graph is to visualize the effect of two independent variables of a specific response. In last two videos, I have discussed about your question.
Thanks very much for these videos- I have seen the previous ones too- very explanatory My question is, how can we account for uncertainties in an experimental design? E.g. if we try to reproduce an experiment and we're getting slight variations in the responses, how do we account for these variations? Thanks
In RSM experiments, the central values do the same. For example, in this case there was six central value treatments (every treatment contain same amount of independent variables or in simple word repetition of treatment). Hence, software can detect the variations or uncertainties in your experiments and predict optimum condition accordingly. Additionally, in confirmatory phase, the values predicted by software are confirmed through running experiment thrice using optimized conditions
thanks a lot. you have explained the design very beautifully.
You are welcome
Hi Teaching Junction - I really appreciate your effort of putting an example that helps explain the basics of the software. Please let me know if I can connect with you over linked-in or email. I have some questions on design of experiments, or if I can hire someone who can do that for me. Looking forward to it. Thanks once again.
Thank you for your explanation but I have a question I didn't understand when we first enter the rsponses to do the analysis are those rsponse already predicted as u said after the optimization done we need to perform another experiment to see the difference between predicted and actual response ?? bit confuse 😢😢 and I NEED HELP
The model predict response after optimization step. After optimization RSM predict optimized level of independent variable as well as potential response
@@TeachingJunction Thank you so much😇❤️ I'm following ur design expert to learn it very well explained plz make more detail videos if possible about the each analysis. Then the predicted response after optimization should be very close to what we enter the actual response when we did the experiment but what if it's not?? should we again start from the beginning
Thanks again, is it possible to superimpose 3D curves in a single graph? for example the graph of 6min 32sec
Hi Sir. Is there any Zoom class training secessions? Thanks
How to use design expert software-Introductory video: ua-cam.com/video/SEPEtr6SGSU/v-deo.html
How to know that this 3d graph is right ??? By which changes we can predict ...
You can make 3D graph by keeping in mind the independent variables. If you have 3 independent variables (A, B and C), you can make two 3D graphs of AB and BC for individual response. The purpose of 3D graph is to visualize the effect of two independent variables of a specific response. In last two videos, I have discussed about your question.
Thanks🙇♀️
You're welcome 😊
Anyone knows how to find the constraints of the factors and response? And a suggested solution.
Thanks a lot!
You're welcome!
Thanks very much for these videos- I have seen the previous ones too- very explanatory
My question is, how can we account for uncertainties in an experimental design?
E.g. if we try to reproduce an experiment and we're getting slight variations in the responses, how do we account for these variations?
Thanks
In RSM experiments, the central values do the same. For example, in this case there was six central value treatments (every treatment contain same amount of independent variables or in simple word repetition of treatment). Hence, software can detect the variations or uncertainties in your experiments and predict optimum condition accordingly. Additionally, in confirmatory phase, the values predicted by software are confirmed through running experiment thrice using optimized conditions
Sir how can I download doe crack version software in my laptop ... Do u know pls help me I have to submit project and result
Unfortunately, I do not have any information about that. But, you can get trail version of design expert free for 30 days
@@TeachingJunction thnku
@@TeachingJunction can u provide the link for trial
You can request for trail version from this link www.statease.com/software/design-expert/