iSixSigma

Mode

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  • #39099

    ROSS
    Member

    Hi,
        What is the meaning of “Mode” in Minitab?
     Tks!

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    #118170

    BTDT
    Participant

    Found the definition here at Dr. Math. It means the same here as it
    does in Minitab.
    http://mathforum.org/library/drmath/sets/mid_statistics.html

    0
    #118172

    ROSS
    Member

    BTDT,
        Thank you very much! But do you know how can we get mode in Minitab?
     Tks!

    0
    #118200

    faceman
    Participant

    If you have categorical data use Tables > Cross Tabulation or Stats > Basic Statistics > Display Descriptive statistics.  The category with the highest count is your ‘mode’.  I am not sure that it is called a mode in formal statistics if it is categorical data but this would find the ‘most frequent value’ therefore it is conceptually the mode anyway.  You could find it graphically by doing a Pareto or a histogram.  If your categorical data is ordinal then using a Pareto might be a ‘screwy’ way to present the data.
     
    If your data is continuous the easiest way would be to construct a histogram paying attention to the number bins you use.  The highest bar of the histogram would be the ‘bin’ highest observed frequency thusly it would be a reasonable estimate of the ‘mode’.  You are really forcing continuous to discrete in this method in order to find the mode.
    Do you have a good example of a real world situation where the mode is the most appropriate measure of location?  I have usually used mean or median.  But I teach the concept of mode in week one but I am lacking a REAL example of where it is the most rational measure of location (for continuous data anyway).
    Regards,
    faceman

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    #118207

    BTDT
    Participant

    I agree with Faceman that ‘mode’ is not really to be used directly with continuous data. The data must be ‘binned’ before talking about the mode. This is done automatically when doing a histogram or using the graphical summary in Minitab.
    It is common, however, to talk about the distribution of continuous data as ‘unimodal’ or ‘bimodal’ depending on the shape of the histogram. The data does not strickly have two modes, but it is still a common way to describe continuous data that shows two humps in a histogram.
    The mode is one of the four indications of central tendency (mean, median, mode and midrange).
    BTDT

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