IQSS Beamer Class Demonstration

In binb: 'binb' is not 'Beamer'

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

# Say hello in R
hello <- function(name) paste("hello", name)

# Say hello in Python
def hello(name):
return("Hello" + " " + name)

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

/* 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
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

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

knitr::kable(mtcars[1:5, 1:8],
             caption="(Parts of) the mtcars dataset")

Resources

For more information:

• See the IQSS repository for more on the IQSS them
• See the RMarkdown repository for more on RMarkdown
• See the binb repository for more on binb
• See the binb vignettes for more examples.

binb documentation built on July 2, 2020, 4:08 a.m.