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HW1.nb
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Cell[CellGroupData[{
Cell["SDS 384.7 HW1", "Title",
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Cell["Qi Chen(qc586)", "Author",
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Population: A set of similar items or events which is of interest for some \
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Population Data: The collection of data that describes similar items or \
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Parameter: Numerical descriptive measures to characterize distribution \
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Statistic: A statistic is a function of the observable random variables in a \
sample and known constants.\
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Statistics: A branch of mathematics dealing with the collection, analysis, \
interpretation, and presentation of masses of numerical data. Its objective \
is inference making.\
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Sampling distribution of a statistic in classical / frequentist inference.: \
The probability distribution of a statistic of sample random variables that \
describes the relative frequency of making the same observation in a large \
number of sampling experiments.\
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Test statistic in classical / frequentist inference.: Test of a statistical \
hypothesis based on the frequency or proportion of the data.\
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P-value in classical / frequentist inference.: The p-value is defined based \
on the frequency or proportion of the data as the smallest probability for \
which the observed data indicate that the null hypothesis should be rejected.\
\
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"Random sample: Let ",
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i.i.d data/random variables: A random variable is a real-valued function for \
which the domain is a sample space.\
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"C.L.T for the sample average: Let ",
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" has the following limit:"
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Explain why P-value in classical / frequentist inference is a frequentist \
summary.\
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Cell["\<\
Solution: p-value in classical/frequentist inference is the probability of \
obtaining a value for the test statistic that is at least as extreme as the \
one that was actually observed, assuming that the null hypothesis is true. In \
large sampling, p-value is the relative frequency of the times the values are \
at least as extreme as the one that was observed. As a result, it is a \
frequentist summary of the test statistic.\
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Reverend Thomas Bayes, the inventor of Bayes Theorem, and the French \
mathematician Laplace addressed this problem in the 18th century: how should \
we estimate the proportion of female births, \[Theta], in a population? In \
one data set from that era, a total of 241945 girls were observed in a sample \
of 493472 births in Paris from 1745 to 1770. Find a classical/frequentist 95% \
confidence interval for \[Theta] and give its interpretation.\
\>", "TextNoIndent",
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"for large n, the proportion \[Theta] is the sample average ",
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In the context of question #3, pretend that in another random sample of 100 \
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All are girls. What does the classical/frequentist 95% confidence interval \
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All are boys. What does the classical/frequentist 95% confidence interval \
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Consider the set of the annual incomes of all full-time employees of \
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