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Normalization, reweighting, and the scale factor:

  1. Jan 30, 2010 #1
    Hi all,

    I am about to begin my studies as an experimentalist and I keep hearing about these terms when someone represents his data as histograms.
    Can some one here, please, give me a clear explanation about their meanings.
    My background is theory and you can use as much mathematics as you can!

    Thanks a lot in advance,

  2. jcsd
  3. Jan 30, 2010 #2
    normalization: generally this term comes in spectrum...after getting a experimental spectrum one often normalize it...experimental spectrum and normalized spectrum are same but with different y-axis value..for e.g., area of a exp. spectrum is different from normalized spectrum..usually a normalized one's area is often 1 or some value.
    reweighting..:similar to normalization..it depends on experiment.
    scale factor: usually multiplying either x- or y-axis by a constant.
    hope this help
  4. Jan 30, 2010 #3
    To make things eaiser, let's say you are in a a particle physics experiment that is trying to discover a particle.
    Now, for normalization, how can we make the area under the histogram equal one?
    Can you elaborate more on reweighting? What is the difference between reweighting (to Monte Carlo) and normalization?

  5. Jan 30, 2010 #4
    normalization(actually this is a general technique used everywhere not only for particle physics):
    think..we have a exp. spectrum [tex]\int I(E)\;{\rm d}E=X[/tex]
    now we will normalize that spectrum such that area under the spectrum is 1.
    So what ppl. usually do is
    [tex]\int I_{\rm norm}(E)\;{\rm d}E=\frac{1}{X}\int I(E)\;{\rm d}E=1[/tex]
    This is how a normalization done.[but i am not completely sure..i assume others from this forum may correct us in case of error.]
    Now i can give a example for weighing (i dont know exactly what is reweighing?).
    in this integral:
    [tex]\int \frac {I(E)}{E}\;{\rm d}E[/tex]
    [tex]I(E)[/tex] is weighed by a factor of [tex](1/E)[/tex]
    hope it may help..
    Last edited: Jan 30, 2010
  6. Jan 31, 2010 #5
    Thank you Rajini,

    So, I am OK now with normalization! Still I hope someone here will explain reweighting for us.
    As far as I know, reweighting is to divide the number of events in each bin of a histogram by the total number of events. If this is true, then why do we need to do reweighting?

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