Update to PreTeXt project source.
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@@ -356,17 +356,17 @@
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</p>
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</answer>
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</exercise>
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<!-- <exercise>
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<!--
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<exercise>
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<statement>
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<p>
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Each of 10 toxin molecules inside a cell has a 0.3 probability of leaving the cell during a 1-minute period.
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For each value of <m>n = 1, 2, 3, \dotsc</m>, and for each value of <m>0\leq k \leq n</m>, find the probability that exactly <m>k</m> toxin molecules remain in the cell after the <m>n</m>th minute.
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</p>
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</statement>
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</exercise> -->
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</exercise>
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<!-- TODO write a solution --> <exercisegroup>
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--> <!-- TODO write a solution --> <exercisegroup>
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<introduction>
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<p>
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In each of the following scenarios with given events <m>A</m> and <m>B</m>, alculate <m>\Pr(A), \Pr(B)</m>, <m>\Pr(A\cap B)</m>, <m>\Pr(A \mid B)</m>, and <m>\Pr(B \mid A)</m>.
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@@ -1126,5 +1126,45 @@
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</p>
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</statement>
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</exercise>
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<exercise>
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<statement>
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<p>
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Suppose a coin has an unknown probability of coming up heads.
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We perform the experiment in <m>n</m> independent trials, during which it takes <m>k_1, k_2, \dotsc, k_n</m> flips to see our first heads in each trial.
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Find a "common sense" MLE formula for the geometric distribution.
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</p>
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</statement>
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</exercise>
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<exercise>
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<statement>
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<p>
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A particular store owner wants to approximate the average hourly rate at which customers come into the store.
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They observe 80 customers enter during a particular 4-hour shift.
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What is the maximum likelihood estimation for the hourly customer rate?
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</p>
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</statement>
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</exercise>
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<exercise>
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<statement>
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<p>
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A radioactive material emits particles at an unknown probabilistic rate <m>\lambda</m> particles per minute.
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We observe particles emitted at times 1.1, 1.7, 1.3, 2.2, 1.9, and 1.8 minutes.
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Write the likelihood function <m>\mathcal{L}(\lambda)</m> based on this data.
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What is the maximum likelihood estimation for <m>\lambda</m>?
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</p>
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</statement>
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</exercise>
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<exercise>
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<statement>
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<p>
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Suppose a parameter <m>\theta</m> takes values in <m>[0, 1]</m> with likelihood function <m>\mathcal{L}(\theta) = \sqrt{\theta} - \theta^2</m>.
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Find the maximum likelihood estimation of <m>\theta</m>.
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</p>
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</statement>
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</exercise>
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</exercises>
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</section>
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