Regression was not needed for this data. Especially the regression model was not significant. Thus, the linear model was not fit for the data. Anyway, thank you. I know it was just an example.
Hey Arun I am new to this method. Can u plz tell me how to select level values for example if I want to optimize the effect of Magnesium and Tungsten in growth fermentation. How will I select the values to optimize by this method.
Sir, all the p values are greater than 0.05 does that mean that those factors are insignificant. I performed an experiment and on analysis I am getting p values greater than 0.05, what should one do in such a case. I need to present a report so please tell me what to do.
I was told that high p values can be due to less gaps in level selection. Speed: 450, 1100, 1500 Feed: 0.2, 0.4, 0.6 Doc: 0.3, 0.6, 1.0 I think the ranges are broad enough. Can you help me please?
Usually, a significance level (denoted as α or alpha) of 0.05 works well. A significance level of 0.05 indicates a 5% risk of concluding that the coefficient is not 0 when it is. If the p-value is greater than the significance level, you cannot conclude that there is a statistically significant association between the response characteristic and the term. You may want to refit the model without the term
Thank you for explaining Taguchi Design. I have some question. In your analysis R2 is very low and in pareto analysis all factors found significant effect. Is it good model for designing an experiment. What is the meaning of delta value in taguchi design?.Thank you in advance.
some papers provide K or/and k values as well as R values (k1, k2, k3). how do we calculate and find those values? Or are those values based on the response table of SN ratios and Means ?
No, actually the K values are expressed from the variables or the parameters of the case and the R values calculated from it, if the signal to ratio design is the larger the better you can rank the significant variables effect from it, you can also choose another design, the signal-to-noise (S/N) ratio measures how the response varies relative to the nominal or target value under different noise conditions, I hope my explanation is sufficient for you, otherwise, you can find somebody else with clearer and better explanation
@@scienceroast9558 so in your above case, how do u calculate the K (k1, k2, k3) values in your design? Is that calculated by minitab app or are/is there a formula ?
@@scienceroast9558 because I don’t see any K value on your factor design for (Rice, Fish, Meat). FYI, I’m also working on taguchi design for food preservation technology.
@@andisyahrullah those variables actually the K's, I just put the easiest case so people can understand easily for this method, sometimes people are too difficult to understand academic or statistic language
Regression was not needed for this data. Especially the regression model was not significant. Thus, the linear model was not fit for the data. Anyway, thank you. I know it was just an example.
Sir, what's the function of KM Distance in this example? How do you get the value of KM Distance?
Based on the trail of L9, they have measured the value manually by one by one study
Why there is no standard deviation?? Mean plot and SN ratio were same.. Is it the same case for all larger the better equations?
that was realy a good video,i'm from INDIA working on taguchi method. it was really a helpful video
Hey Arun I am new to this method. Can u plz tell me how to select level values for example if I want to optimize the effect of Magnesium and Tungsten in growth fermentation. How will I select the values to optimize by this method.
Sir, all the p values are greater than 0.05 does that mean that those factors are insignificant. I performed an experiment and on analysis I am getting p values greater than 0.05, what should one do in such a case. I need to present a report so please tell me what to do.
I was told that high p values can be due to less gaps in level selection.
Speed: 450, 1100, 1500
Feed: 0.2, 0.4, 0.6
Doc: 0.3, 0.6, 1.0
I think the ranges are broad enough. Can you help me please?
Usually, a significance level (denoted as α or alpha) of 0.05 works well. A significance level of 0.05 indicates a 5% risk of concluding that the coefficient is not 0 when it is. If the p-value is greater than the significance level, you cannot conclude that there is a statistically significant association between the response characteristic and the term. You may want to refit the model without the term
how we got the response km from excel....in my excel i didn had any data available..can you please help sir
(2)
May I get the link for research paper
Very nice explanation,
Well done; thank you. One question though: your variables have 3 levels (Categories I assume). Why did you select theme as "Continous". Thank you :)
Hi! Do you possibly know anyone I can speak to about Taguchi method? I need a mentor T.T Having a problem
nice video,
tip: watch this video @ 1.5 playback speed !
please give me specific guidance on analyzing optimization parameters, thanks!
This is so good. I would like to learn more about this in the future for my PhD topic. Thank you.
It seems that the Rsq is too small indicating that the range of x factors are not adding value to the model.
do you have L8 (2^7) example?
Thank you for explaining Taguchi Design. I have some question. In your analysis R2 is very low and in pareto analysis all factors found significant effect. Is it good model for designing an experiment. What is the meaning of delta value in taguchi design?.Thank you in advance.
Thank you for the comment, this video is meant to display the tutorial only, not the interpretation, the interpretation will be very soon
Great stuff! My question is how did we determine that we are going to use L9 array since we had (3^3) 3 levels and 3 factors
depends on what you want, 9 or 27, my supervisor told me just to make 9 because hes lazy lmao. so do i
thankyouuu you are the best
Thank you very much
thanks
Simple and clear explanation thank you.
Thank you
some papers provide K or/and k values as well as R values (k1, k2, k3). how do we calculate and find those values? Or are those values based on the response table of SN ratios and Means ?
No, actually the K values are expressed from the variables or the parameters of the case and the R values calculated from it, if the signal to ratio design is the larger the better you can rank the significant variables effect from it, you can also choose another design, the signal-to-noise (S/N) ratio measures how the response varies relative to the nominal or target value under different noise conditions, I hope my explanation is sufficient for you, otherwise, you can find somebody else with clearer and better explanation
@@scienceroast9558 so in your above case, how do u calculate the K (k1, k2, k3) values in your design? Is that calculated by minitab app or are/is there a formula ?
@@scienceroast9558 because I don’t see any K value on your factor design for (Rice, Fish, Meat). FYI, I’m also working on taguchi design for food preservation technology.
@@andisyahrullah those variables actually the K's, I just put the easiest case so people can understand easily for this method, sometimes people are too difficult to understand academic or statistic language
Thanks
Thank you
Well done
Thank you Doc
I see that your P-values are higher than alfa (0,05). Is there something wrong with your analyses ?
Yeah, it's just a tutorial to do it step by step, don't mind the result, for the interpretation it will be on the next video
@@scienceroast9558 thank you !