QB/d Bell.binomial
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 This is a conceptual quiz that should not require a calculator.
 See also A card game for Bell's theorem and its loopholes/Conceptual
 The instructor may wish to show students File:Standard deviation diagram.svg for reference as they take this quiz.
 See Talk:QB/d Bell.binomial for answers with explanations
 See special:permalink/1945670 for a wikitext version of this quiz.
See special:permalink/1882674 for a wikitext version of this quiz.
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Attribution for each question is documented in the Appendix}
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\question The normal distribution (often called a "bell curve") is never skewed\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\question The normal distribution (often called a "bell curve") is usually skewed\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\question By definition, a skewed distribution\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
\begin{choices}
\choice is broader than an unskewed distribution
\choice includes negative values of the observed variable
\choice is a "normal" distribution
\CorrectChoice is asymmetric about its peak value
\choice contains no outliers
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\question The binomial distribution results from observing n outcomes, each having a probability p of "success"\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\question What is the probability of success, p, for a binary distribution using a sixsided die, with success defined as "two"?\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 3/6
\choice 2/6
\CorrectChoice 1/6
\choice 5/6
\choice 4/6
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\question What is the probability of success, p, for a binary distribution using a sixsided die, with success defined as anything but "two"?\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 2/6
\choice 1/6
\CorrectChoice 5/6
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\question What is the probability of success, p, for a binary distribution using a sixsided die, with success defined as either a "two" or a "three"?\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 3/6
\CorrectChoice 2/6
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\choice 5/6
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\question How would you describe the "skew" of a binary distribution?\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\CorrectChoice The binary distribution is always skewed, but has little skew for a large number of trials n.
\choice The binary distribution is always skewed, but has little skew for a small number of trials n.
\choice The binary distribution is never skewed if it is a true binary distribution.
\choice Distributions are never skewed. Only experimental measurements of them are skewed.
\choice None of these are true.
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\question For a binomial distribution with n trials, the variance is \textsigma\ \textsuperscript{2}=np(1p). If 90 trials are observed, then 68\% of the time the observed number of positive outcomes will fall within \(\pm\)\_\_\_ of the expected value if p=.11 is the probability of a positive outcome. Make the approximation that this binomial distribution is approximately a Gaussian (normal) distribution).\ifkey\endnote{CCO [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\question For a binomial distribution with n trials, the variance is \textsigma\ \textsuperscript{2}=np(1p). If 40 trials are observed, then 68\% of the time the observed number of positive outcomes will fall within \(\pm\)\_\_\_ of the expected value if p=.11 is the probability of a positive outcome. Make the approximation that this binomial distribution is approximately a Gaussian (normal) distribution).\ifkey\endnote{CCO [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\question For a binomial distribution with n trials, the variance is \textsigma\ \textsuperscript{2}=np(1p). If 40 trials are made and p=.11, the expected number of positive outcomes is\_\_. Make the approximation that this binomial distribution is approximately a Gaussian (normal) distribution.\ifkey\endnote{CCO [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\question For a binomial distribution with n trials, the variance is \textsigma\ \textsuperscript{2}=np(1p). If 90 trials are made and p=.11, the expected number of positive outcomes is\_\_. Make the approximation that this binomial distribution is approximately a Gaussian (normal) distribution.\ifkey\endnote{CCO [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 2.2
\CorrectChoice 9.9
\choice 3.3
\choice 1.1
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\question Recall that only 4.6\% of the outcomes for a normal distribution lie outside of two standard deviations from the mean, and approximate the binomial distribution as normal for large numbers. If the variance is \textsigma\ \textsuperscript{2}=np(1p) where n is the number of trials and p=.11 is the probability of a positive outcome for 40 trials, roughly 98\% of the outcomes will be smaller than approximately \_\_\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 12
\choice 16
\choice 22
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\question Recall that only 4.6\% of the outcomes for a normal distribution lie outside of two standard deviations from the mean, and approximate the binomial distribution as normal for large numbers. If the variance is \textsigma\ \textsuperscript{2}=np(1p) where n is the number of trials and p=.11 is the probability of a positive outcome for 90 trials, roughly 98\% of the outcomes will be smaller than approximately \_\_\ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 6
\choice 8
\choice 12
\CorrectChoice 16
\choice 22
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\question A local college averages 2500 new incoming students each year. Suppose the pool of potential high school graduates in the local area is so large that the probability of a given student selecting this college is small, and assume a variance of \textsigma\ \textsuperscript{2} equal to p(1p). What standard deviation would you expect in the yearly total of new enrollees, assuming nothing changes in this population from year to year? \ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 150
\choice 500
\choice 200
\choice 250
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\question A local college averages 1600 new incoming students each year. Suppose the pool of potential high school graduates in the local area is so large that the probability of a given student selecting this college is small, and assume a variance of \textsigma\ \textsuperscript{2} equal to p(1p). What standard deviation would you expect in the yearly total of new enrollees, assuming nothing changes in this population from year to year? \ifkey\endnote{CC0 [[user:Guy vandegrift]] placed in Public Domain by Guy Vandegrift: {\url{https://en.wikiversity.org/wiki/special:permalink/1882674}}}\fi
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\choice 160
\CorrectChoice 40
\choice 10
\choice 32
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\section{Attribution}
\theendnotes
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