\documentclass[xcolor=dvipsnames,t,aspectratio=169]{beamer} %t para ficar alinhado no topo do slide
\usecolortheme{rose}
\usecolortheme{dolphin}
\usetheme{Boadilla}
\input{imports}
\input{settings}
\input{commands}
\titlegraphic{
\includegraphics[scale = 0.25]{emap_logo}
}
\logo{
\begin{tikzpicture}[overlay,remember picture]
\node[left=1.1cm, below=0.2cm] at (current page.30){
\includegraphics[width=0.165\textwidth]{emap_logo}};
\end{tikzpicture}
}
\lstset{style=mystyle}
\newcommand{\highlight}[1]{{\color{fgv_light_blue} #1}}
\title{Your Title Here}
\author{
\newauthor{Crazy Frog}{crazy.frog@music.br}
\newauthor{Michael Jackson}{whosbad@music.br} % Just remove if not wanted
% you can fill up to 6 authors
}
\date{{\color{fgv_dark_blue} \textbf{Your Place Here}\\ Your Date Here }}
\begin{document}
\frame[plain]{\titlepage}
\setcounter{framenumber}{0}
\begin{frame}[c]{Slide Title}
Welcome to \LaTeX\ Beamer FGV EMAp Template, a \LaTeX\ Beamer Template specifically designed for use by students and faculty at \href{https://emap.fgv.br/en}{FGV EMAp}. This template provides an easy and efficient way to create beautifully formatted presentations, maintaining the aesthetic and quality standards of our institution.
\begin{display}[Block Title]
You can use the command \highlight{highlight} to have \highlight{emphasize} some words.
\end{display}
This template is first updated on its \href{https://github.com/adamesalles/latex-beamer-emap}{GitHub repository}, take a look and give a star if you could.
\end{frame}
\begin{frame}[c]{Mathematics}
\begin{theo}{Weak Law of Large Numbers}{wlln} % env, title, label
Let $\rs$ be a random sample of size $n$ from a distribution with mean $\mu$ and variance $\sigma^2$. Then, for any $\epsilon > 0$,
\begin{equation*}
\pr\left[\left|\frac{1}{n}\sum_{i=1}^n X_i - \mu\right| > \epsilon\right] \to 0 \text{ as } n \to \infty.
\end{equation*}
In other words, $\frac{1}{n}\sum_{i=1}^n X_i \probto \mu$.
\end{theo}
\end{frame}
\begin{frame}[c]{Mathematics}
\begin{defi}{Consistency}{cons}
Let $\hat{\theta}_n$ be an estimator of $\theta$. We say that $\hat{\theta}_n$ is \highlight{consistent} if $\hat{\theta}_n \probto \theta$.
\end{defi}
\begin{remark}{}{}
Theorem \ref{theo:wlln} together with Definition \ref{defi:cons} implies that the sample mean is a consistent estimator of the population mean.
\end{remark}
\end{frame}
\begin{frame}[c]{Mathematics}
\begin{proof}[Theorem \ref*{theo:wlln}] % proof carries only title
Let $\epsilon > 0$. By Chebyshev's inequality,
\begin{equation*}
\pr\left[\left|\frac{1}{n}\sum_{i=1}^n X_i - \mu\right| > \epsilon\right] \leq \frac{\sigma^2}{n\epsilon^2}.
\end{equation*}
Since $\sigma^2$ is a constant, the result follows.
\end{proof}
\end{frame}
\begin{frame}[c]{Mathematics}
Other useful envs could be:
\begin{ex}{Example Title}{ex1}
This is an example.
\end{ex}
\begin{lem}{Lemma Title}{lem1}
This is a lemma.
\end{lem}
\end{frame}
\begin{frame}[c, fragile]{Coding}
\begin{code}[Example of Code]{python}
import numpy as np
def c(r):
return np.pi*r**2
\end{code}
\end{frame}
\begin{frame}[c, noframenumbering, plain]
\frametitle{~}
\vfill
\begin{center}
{\Huge Thanks!}\vspace{1.5em}\\
{\Large \highlight{Any thoughts?}}\\
\end{center}
\vfill
\begin{center} % Change your thanks
{\small Special thanks to \href{https://yurisaporito.com}{prof. Yuri Saporito} for providing the early version of this template in 2021.
I would also like to thank \href{https://github.com/maxbiostat}{prof. Luiz Max de Carvalho}, which inspired me to publish this repo - even though it is still a work in progress.
Finally, thanks to \href{https://matematicaeparatodos.com/}{Tulio Koneçny}, \href{https://github.com/dccsillag}{Daniel Csillag} and \href{https://emap.fgv.br/en/professors/claudio-jose-struchiner}{prof. Claudio Struchiner} for their suggestions.}
\end{center}
\begin{figure}[!b] % feel free to thank me.
\begin{flushright}
\small Template by Eduardo Adame\\ \highlight{adamesalles.github.io}
\end{flushright}
\end{figure}
\end{frame}
\end{document}
