---
author: Ista Zahn and Gary King
classoption: compress
fontsize: 12pt
title: IQSS Beamer Class Demonstration
date: \today
institute: IQSS 
output: binb::iqss
---


# Beamer Features

## Some of Gary's Examples

### What's this course about? 

- \alert{Specific statistical methods for many research problems}
      - How to learn (or create) new methods
      - Inference: \underline{Using facts you know to learn about
        facts you don't know}
- \alert{How to write a publishable scholarly paper}
- \alert{All the practical tools of research} --- theory,
    applications, simulation, programming, word processing, plumbing,
    whatever is useful
- $\leadsto$ \alert{Outline and class materials:}
    - \mbox{{\huge\parbox[b][.5in][t]{1in}{\alert{j.mp/G2001}}}
        $\qquad\qquad$\includegraphics[width=.95in]{figs/phbAr.png}}
    - The syllabus gives topics, not a weekly plan.
    - We will go as fast as possible subject to everyone following along
    - We cover different amounts of material each week

### How much math will you scare us with?

- All math requires two parts: \alertb{proof} and \alertb{concepts \& intuition}
- Different classes emphasize:
    - \alert{Baby Stats}: dumbed down proofs, vague intuition
    - \alert{Math Stats}: rigorous mathematical proofs
    - \alert{\underline{Practical Stats}}: deep concepts and intuition, proofs when needed
        - Goal: how to do empirical research, in depth
        - Use rigorous statistical theory --- when needed
        - Insure we understand the intuition --- always
        - Always traverse from theoretical foundations to practical applications
        - Includes ``how to'' computation
        - $\leadsto$ Fewer proofs, more concepts, better practical knowledge
- Do you have the background for this class? 
\alert{A Test: What's this?
    \begin{align*}
      b=(X'X)^{-1}X'y
    \end{align*} }


### Systematic Components: Examples

\includegraphics[width=8cm]{figs/functionalForms}

- \alertb{$E(Y_i) \equiv \mu_i = X_i\beta = \beta_0 +
      \beta_1X_{1i} +\dots+\beta_kX_{ki}$}
- \alertc{$\Pr(Y_i=1) \equiv \pi_i =
      \frac{1}{1+e^{-x_i\beta}}$}
- \alertd{$V(Y_i)\equiv \sigma_i^2 = e^{x_i\beta}$}
- Interpretation:
    - Each is a \alert{class of functional forms}
    - Set $\beta$ and it picks out one \alert{member of the class}
    - \alert{$\beta$} in each is an ``effect parameter'' vector,
      with different meaning


### Code blocks

\footnotesize

```r
# Say hello in R
hello <- function(name) paste("hello", name)
```
 
```python
# Say hello in Python
def hello(name):
return("Hello" + " " + name)
```

```haskell
-- Say hello in Haskell
hello name = "Hello" ++ " " ++ name
```

```c
/* Say hello in C */
#include <stdio.h>
int main()
{
  char name[256];
  fgets(name, sizeof(name), stdin);
  printf("Hello %s", name);
  return(0);
}

\normalsize


### Alerts

- First level \alert{alert}
- Second level \alertb{alert}
- Third level \alertc{alert}
- Fourth level \alertd{alert}
- Fifth level \alerte{alert}

# More Features 

## Blocks

### Other Features

#### Levels of Structure

- Clean, extensively customizable visual style
- Hyperlinks ([http://github.com/izahn/iqss-beamer-theme](click here_) 
- No weird scaling prosper
    - slides are 96~mm~$\times$~128~mm
    - text is 10-12pt on slide
    - slide itself magnified with Adobe Reader/xpdf/gv to fill screen
- pgf graphics framework easy to use
- include external JPEG/PNG/PDF figures
- output directly to pdf: no PostScript hurdles
- detailed User Manual (with good presentation advice, too)


### Theorems and Proofs
\framesubtitle{The proof uses \textit{reductio ad absurdum}.}

#### Theorem
There is no largest prime number.

#### Proof
> - Suppose $p$ were the largest prime number.
> - Let $q$ be the product of the first $p$ numbers.
> - Then $q+1$ is not divisible by any of them.
> - But $q + 1$ is greater than $1$, thus divisible by some prime
    number not in the first $p$ numbers. \qedhere

### Blocks

#### Normal block
A \alert{set} consists of elements.


#### \alert{Alert block}
$2=2$.

#### \alertc{Example block}
The set $\{1,2,3,5\}$ has four elements.

# RMarkdown Examples

### R Figure 

The following code generates the plot on the next slide (taken from
`help(bxp)` and modified slightly):

```{r pressureCode, eval=FALSE}
library(stats)
set.seed(753)
bx.p <- boxplot(split(rt(100, 4),
                      gl(5, 20)), plot=FALSE)
bxp(bx.p, notch = FALSE, boxfill = "lightblue",
    frame = FALSE, outl = TRUE,
    main = "Example from help(bxp)")
```  


### R Figure 
  
```{r pressureFig, echo=FALSE}
library(stats)
set.seed(753)
bx.p <- boxplot(split(rt(100, 4),
                      gl(5, 20)), plot=FALSE)
bxp(bx.p, notch = FALSE, boxfill = "lightblue",
    frame = FALSE, outl = TRUE,
    main = "Example from help(bxp)")
```  

### R Table 
  
A simple `knitr::kable` example:  

\small

```{r kableEx}
knitr::kable(mtcars[1:5, 1:8],
             caption="(Parts of) the mtcars dataset")
```

### Resources

#### For more information:
- See the [IQSS repository](https://github.com/IQSS/iqss-beamer-theme) for more on the IQSS them
- See the [RMarkdown repository](https://github.com/rstudio/rmarkdown) for more on RMarkdown
- See the [binb repository](https://github.com/eddelbuettel/binb) for more on binb 
- See the [binb vignettes](https://github.com/eddelbuettel/binb/vignettes) for more examples.
