Understanding Standard Deviation and Variance in estimates

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This topic contains 1 reply, has 1 voice, and was last updated by  Jo Youngblood 5 years, 9 months ago.

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  • #156447

    Travis K. Anderson
    Participant

    I was wondering if someone could help me to understand what story standard deviation and variance should tell the estimator.

    Formulas:

    PERT: (O+4ML+P)/6

    Std Dev: (P-O)/6

    Variance: (P-O/6)^2

    Example:

    In the example below the we are calculating 1 Std Dev from the mean, i.e. the PERT value. Therefore there is a 68% certainty the estimate is 160.83 +/- 8.33 (152.5 to 169.16). At 95% the estimate is 160.83 +/- 2 * 8.33 (144.17 to 177.49).

    So now what?

    How do I distinguish a favorable Std Dev from a un-favorable Std Dev?

    What is the Variance telling me?

    How do I apply this to my final estimate?

    Etc…

    O ML P PERT Std Dev Var
    150 160 175 160.83 8.33 69.44
    125 130 135 130.00 1.67

    2.78

  • #156449

    Jo Youngblood
    Participant

    Well I typically find it useful to analyze standard deviations and variance by looking at a whole picture of data points. Two points may or may not give you a good idea. But what I notice is that as O increases so does your variance and standard deviation. This may indicate that your error measurement is not standard across all measures but has an interaction term with O (ie. there may be another variable or interaction term missing in your prediction formula).

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