lectures 11: maximum likelihood iv. (nonlinear least...
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Lectures 11: Maximum likelihood IV.(nonlinear least square fits)
𝜒2 fitting procedure!
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increasing temperature x in some arbitrary units
measured value of 2p-0.4 as a function of x
x
from Lecture 9:
= 2·p(x) - 0.4 = y(x|b)
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Maximum Likelihood discussionfrom Lecture 9:
frequentist: P(b) ~ δ(b-b0) b0?
Bayesian: P(b) ~ const simplest,leads to same b0 determination
repeating the experiment with yi and 𝜎i we also test f(x) as a hypothesis
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increasing temperature x in some arbitrary units
from Lecture 9: Maximum Likelihood discussion
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Maximum Likelihood parameter errors?from Lecture 9:
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Maximum Likelihood parameter errors?
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Maximum Likelihood parameter errors?
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𝜒2 distribution goodness of fit
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confidence intervals
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𝜒2 distribution (from Lecture 10)
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𝜒2 distribution
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confidence intervals
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what is the Degree of Freedom?
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what is the Degree of Freedom?
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what is the Degree of Freedom?
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what is the Degree of Freedom?
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Goodness-of-fit
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