Neyman-Pearson lemma with pdf of $X$ vs Neyman-Pearson Lemma with likelihood functions












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As written in the subject line, I’m confused about the statement made in the Neyman-Pearson Lemma, largely because one of my two textbooks states the Lemma in terms of the pdf of $X$ while the other textbook states the Lemma in terms of the likelihood function of $X$. I don’t believe that the two statements are logically equivalent. Any thoughts on this discrepancy?










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  • $begingroup$
    If you have a sample $X=(X_1,ldots,X_n)$, then it is the joint density of $(X_1,ldots,X_n)$ (likelihood function) and if you have a single observation $X$ (i.e. for $n=1$), then it is the pdf of $X$. What's the difference?
    $endgroup$
    – StubbornAtom
    Nov 29 '18 at 15:46


















0












$begingroup$


As written in the subject line, I’m confused about the statement made in the Neyman-Pearson Lemma, largely because one of my two textbooks states the Lemma in terms of the pdf of $X$ while the other textbook states the Lemma in terms of the likelihood function of $X$. I don’t believe that the two statements are logically equivalent. Any thoughts on this discrepancy?










share|cite|improve this question









$endgroup$












  • $begingroup$
    If you have a sample $X=(X_1,ldots,X_n)$, then it is the joint density of $(X_1,ldots,X_n)$ (likelihood function) and if you have a single observation $X$ (i.e. for $n=1$), then it is the pdf of $X$. What's the difference?
    $endgroup$
    – StubbornAtom
    Nov 29 '18 at 15:46
















0












0








0





$begingroup$


As written in the subject line, I’m confused about the statement made in the Neyman-Pearson Lemma, largely because one of my two textbooks states the Lemma in terms of the pdf of $X$ while the other textbook states the Lemma in terms of the likelihood function of $X$. I don’t believe that the two statements are logically equivalent. Any thoughts on this discrepancy?










share|cite|improve this question









$endgroup$




As written in the subject line, I’m confused about the statement made in the Neyman-Pearson Lemma, largely because one of my two textbooks states the Lemma in terms of the pdf of $X$ while the other textbook states the Lemma in terms of the likelihood function of $X$. I don’t believe that the two statements are logically equivalent. Any thoughts on this discrepancy?







statistics statistical-inference hypothesis-testing






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share|cite|improve this question











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asked Nov 28 '18 at 16:52









DavidDavid

337210




337210












  • $begingroup$
    If you have a sample $X=(X_1,ldots,X_n)$, then it is the joint density of $(X_1,ldots,X_n)$ (likelihood function) and if you have a single observation $X$ (i.e. for $n=1$), then it is the pdf of $X$. What's the difference?
    $endgroup$
    – StubbornAtom
    Nov 29 '18 at 15:46




















  • $begingroup$
    If you have a sample $X=(X_1,ldots,X_n)$, then it is the joint density of $(X_1,ldots,X_n)$ (likelihood function) and if you have a single observation $X$ (i.e. for $n=1$), then it is the pdf of $X$. What's the difference?
    $endgroup$
    – StubbornAtom
    Nov 29 '18 at 15:46


















$begingroup$
If you have a sample $X=(X_1,ldots,X_n)$, then it is the joint density of $(X_1,ldots,X_n)$ (likelihood function) and if you have a single observation $X$ (i.e. for $n=1$), then it is the pdf of $X$. What's the difference?
$endgroup$
– StubbornAtom
Nov 29 '18 at 15:46






$begingroup$
If you have a sample $X=(X_1,ldots,X_n)$, then it is the joint density of $(X_1,ldots,X_n)$ (likelihood function) and if you have a single observation $X$ (i.e. for $n=1$), then it is the pdf of $X$. What's the difference?
$endgroup$
– StubbornAtom
Nov 29 '18 at 15:46












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