iSixSigma

Rupesh Lochan

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  • #190845

    Rupesh Lochan
    Member

    Very good inputs. Thanks Robert.
    I was doing the same by coding the attribute variables as 1,2,3,.. etc. I have 2 questions:
    1. What is different when the attribute variable data is ordinal? I will just like to code the levels of x as 1,2 3,4,5
    2. Can’t I get the “Best Subset” out of all the variables ( continous + attribute ), which will take care of multicolinearity and confounding…. and then run regression to get the model ? Your thought ??
    2. Have you used “General Regression” option of Minitab 16. I see the results are not the same as “Regression” option. Why it is so ?

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    #190843

    Rupesh Lochan
    Member

    Let me make myself more clear about the issue.
    I have my Y continuous. I have Xs which have been found signifcant through different hypothesis testing techniquess. There are such 6 Xs in total. Three are continuous and rest three are discrete.
    I am looking for an equation involving all 6 Xs for predicting my Y. Simple linear regression is certainly not applicable since it is an OFAT technique and can take care of only one continuous factor. Multiple regression can take care of more than one factors but all should be continuous.
    Question is: which technique can be used for getting such equation invlving all continuous and dicrete factors together?

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    #190840

    Rupesh Lochan
    Member

    There are lot many case studies available on the net. Pl. ask, if you have a specific problem.

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Viewing 3 posts - 1 through 3 (of 3 total)