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Normalised Histogram

Discussion in 'Mathematics' started by pipipi, Mar 24, 2011.

  1. pipipi

    pipipi New commenter

    are you going to add the normal distribution curve?
  2. bbibbler

    bbibbler New commenter

    Both the histogram and cumulative histogram have
    an additional variant whereby the counts are
    replaced by the normalized counts. The names for these variants
    are the relative histogram and the relative cumulative

    There are two common ways to normalize the counts.

    <ol>[*]The normalized count is the count in a class divided by
    the total number of observations. In this case
    the relative counts are normalized to sum to one
    (or 100 if a percentage scale is used).
    This is the intuitive case where the height of
    the histogram bar represents the proportion of the
    data in each class.

    [*]The normalized count is the count in the class
    divided by the number of observations times the
    class width. For this normalization, the area
    (or integral) under the histogram is equal to one.
    From a probabilistic point of view, this normalization
    results in a relative histogram that is most akin to
    the probability density function and a relative
    cumulative histogram that is most akin to the
    cumulative distribution function. If you want to
    overlay a probability density or cumulative
    distribution function on top of the histogram, use
    this normalization. Although this normalization is
    less intuitive (relative frequencies greater than 1
    are quite permissible), it is the appropriate
    normalization if you are using the histogram to model
    a probability density function.

    The area under the graph is equal to 1
  3. noseygeorge

    noseygeorge New commenter

    Nice one - thank you.

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