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  • #49269

    doe
    Participant

    Forum,
    Do I have this right for 2 level, orthogonal designs for 1st order models….

    Factors of interest can be assessed for significance using among other techniques:  ANOVA or The Interpretability Factor (where the effect is compared to the SE)…are there other ways?
    The unknown parameters of the 1st order model (full, fractional, or PB) are composed – after nonsignificant terms are removed -using a least sq method or by calculating the avg difference in effects (+/-) and dividing it by two..again, other ways for this?
    Using two center points during screening efforts provides both a source of pure error for significant testing used in model reduction as well allowing the detection of curvature (in a 1st order model).
    THANKS!!!!!!!!!!

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    #168181

    clb1
    Participant

    Your first set of questions
    https://www.isixsigma.com/forum/showmessage.asp?messageID=134883
    sounded like homework.
    This set of questions reads like a direct copy from the problem page at the end of the chapter.

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