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\@writefile{toc}{\contentsline {section}{\numberline {1}Distributions}{1}{section.1}}
\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces Getting the functional form of a probability distribution by passing that distribution to the function PDF. If the argument is a variable, in this case $x$, then the function PDF returns a formula. If the argument is a number, PDF returns the value of the probability density function at that point.}}{2}{figure.1}}
\newlabel{fig:PDF}{{1}{2}{Getting the functional form of a probability distribution by passing that distribution to the function PDF. If the argument is a variable, in this case $x$, then the function PDF returns a formula. If the argument is a number, PDF returns the value of the probability density function at that point}{figure.1}{}}
\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces PDF can be used with discrete distributions as well. Here the first cell evaluates the chance of having no successes in six tries, if each individual trial has an eleven percent chance of succeeding. Note in the second cell how the binomial coefficient is written in \emph  {Mathematica}.}}{3}{figure.2}}
\newlabel{fig:PDF-discrete}{{2}{3}{PDF can be used with discrete distributions as well. Here the first cell evaluates the chance of having no successes in six tries, if each individual trial has an eleven percent chance of succeeding. Note in the second cell how the binomial coefficient is written in \emph {Mathematica}}{figure.2}{}}
\@writefile{lof}{\contentsline {figure}{\numberline {3}{\ignorespaces Passing a distribution to the function Random yields a pseudorandom number that, over many iterations, follows that distribution.}}{4}{figure.3}}
\newlabel{fig:Random}{{3}{4}{Passing a distribution to the function Random yields a pseudorandom number that, over many iterations, follows that distribution}{figure.3}{}}
\@writefile{toc}{\contentsline {section}{\numberline {2}Normal Error Integral}{5}{section.2}}
\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces The Normal Error Integral in \emph  {Taylor}'s Appendix\nobreakspace  {}A (bottom area) is the difference of two Cumulative Distribution Functions (top areas).}}{5}{figure.4}}
\newlabel{fig:appa}{{4}{5}{The Normal Error Integral in \emph {Taylor}'s Appendix~A (bottom area) is the difference of two Cumulative Distribution Functions (top areas)}{figure.4}{}}
\@writefile{toc}{\contentsline {section}{\numberline {3}Correlation}{6}{section.3}}
\bibcite{Taylor}{1}
\bibcite{Mathematica}{2}