working on shiny apps

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diff --git a/07_RegressionModels/scratch.Rmd b/07_RegressionModels/scratch.Rmd
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+---
+title       : Scratch work
+subtitle    : 
+author      : Brian Caffo, Jeff Leek and Roger Peng
+job         : Johns Hopkins Bloomberg School of Public Health
+logo        : bloomberg_shield.png
+framework   : io2012        # {io2012, html5slides, shower, dzslides, ...}
+highlighter : highlight.js  # {highlight.js, prettify, highlight}
+hitheme     : tomorrow      # 
+url:
+  lib: ../../libraries
+  assets: ../../assets
+widgets     : [mathjax]            # {mathjax, quiz, bootstrap}
+mode        : selfcontained # {standalone, draft}
+---
+
+---
diff --git a/07_RegressionModels/scratch.html b/07_RegressionModels/scratch.html
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+  <title>Scratch work</title>
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+  <meta name="author" content="Brian Caffo, Jeff Leek and Roger Peng">
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+      <hgroup class="auto-fadein">
+        <h1>Scratch work</h1>
+        <h2></h2>
+        <p>Brian Caffo, Jeff Leek and Roger Peng<br/>Johns Hopkins Bloomberg School of Public Health</p>
+      </hgroup>
+          </slide>
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diff --git a/07_RegressionModels/scratch.md b/07_RegressionModels/scratch.md
@@ -0,0 +1,17 @@
+---
+title       : Scratch work
+subtitle    : 
+author      : Brian Caffo, Jeff Leek and Roger Peng
+job         : Johns Hopkins Bloomberg School of Public Health
+logo        : bloomberg_shield.png
+framework   : io2012        # {io2012, html5slides, shower, dzslides, ...}
+highlighter : highlight.js  # {highlight.js, prettify, highlight}
+hitheme     : tomorrow      # 
+url:
+  lib: ../../libraries
+  assets: ../../assets
+widgets     : [mathjax]            # {mathjax, quiz, bootstrap}
+mode        : selfcontained # {standalone, draft}
+---
+
+---
diff --git a/09_DevelopingDataProducts/shiny/fig/simplestApp.png b/09_DevelopingDataProducts/shiny/fig/simplestApp.png
diff --git a/09_DevelopingDataProducts/shiny/index.Rmd b/09_DevelopingDataProducts/shiny/index.Rmd
@@ -1,103 +1,111 @@
----
-title       : Shiny
-subtitle    : Data Products
-author      : Brian Caffo, Jeff Leek, Roger Peng
-job         : Johns Hopkins Bloomberg School of Public Health
-logo        : bloomberg_shield.png
-framework   : io2012        # {io2012, html5slides, shower, dzslides, ...}
-highlighter : highlight.js  # {highlight.js, prettify, highlight}
-hitheme     : tomorrow      # 
-url:
-  lib: ../../libraries
-  assets: ../../assets
-widgets     : [mathjax]            # {mathjax, quiz, bootstrap}
-mode        : selfcontained # {standalone, draft}
----
-
-## What is Shiny?
-
-- Shiny is a platform for creating interactive R programs embeded into a web page.
-- Suppose that you create a prediction algorith, with shiny you can *very easily* create web input form that calls R and thus your prediction algorithm and displays the results.
-- Using Shiny, the time to create simple, yet powerful, web-based interactive data products in R is minimized.
-  - However, it lacks the flexibility of full featured (and more complex) solutions.
-- Shiny is made by the fine folks at R Studio.
-
----
-## Some mild prerequisites 
-- Shiny doesn't really require it, but as with all web programming, a little knowledge of html, css and js is very helpful
-  - html gives a web page structure and sectioning as well as markup instructions
-  - css gives the style
-  - js for interactivity
-- There are too many tutorials online to count for getting basic proficiency in these topics to count. 
-- Shiny uses [bootstrap](http://getbootstrap.com/) (no relation to the statistics bootstrap) style, which (to me) seems to look nice and renders well on mobile platforms
-
----
-## What else is out there?
-- Full solutions requiring real knowledge of web client/server programming
-- [OpenCPU](https://public.opencpu.org/) by Jerome Ooms, a really neat project providing an API to call 
-
----
-## Context
-- You created a novel prediction algorithm to predict risk for developing
-  diabetes.
-    - You're hoping patients and caregivers will be able to enter their data and, if needed, take preventative measures.
-- You want to create a web site so that users can input the relevant predictors and obtain their prediction.
-- Your prediction algorithm (ok, so you're not going to be saving the world with this one)
-  - (link for a real prediction score)[http://www.ncbi.nlm.nih.gov/pubmed/12610029]
-```{r}
-diabetesRisk <- function(glucose){
-  runif(1)
-}
-```
-
-
----
-## Getting started
-- Great tutorial at 
-(http://rstudio.github.io/shiny/tutorial/)[http://rstudio.github.io/shiny/tutorial/]
-- Basically, this lecture is walking through that tutorial offering some of our insights
-- Note, some of the proposed interactive plotting uses of Shiny could be handled by the very simple `manipulate` function (rstudio manipulate)[http://www.rstudio.com/ide/docs/advanced/manipulate]
-- Also, `rCharts` is will be covered in a different lecture.
-
-```
-install.packages("shiny")
-```
-
-```{r}
-library(shiny)
-```
-
----
-## A Shiny project
-- A shiny project contains two parts
-  - One named ui.R (for user interface) controls how it looks.
-  - One named server.R that controls what it does.
-
----
-## 
-```
-library(shiny)
-shinyUI(pageWithSidebar(
-  headerPanel("Hello Shiny!"),
-  sidebarPanel(
-    sliderInput("obs", 
-                "Number of observations:", 
-                min = 1,
-                max = 1000, 
-                value = 500)
-  ),
-  mainPanel(
-    plotOutput("distPlot")
-  )
-))
-```
-
----
-##
-
-
-
-
-
-
-
+---
+title       : Shiny
+subtitle    : Data Products
+author      : Brian Caffo, Jeff Leek, Roger Peng
+job         : Johns Hopkins Bloomberg School of Public Health
+logo        : bloomberg_shield.png
+framework   : io2012        # {io2012, html5slides, shower, dzslides, ...}
+highlighter : highlight.js  # {highlight.js, prettify, highlight}
+hitheme     : tomorrow      # 
+url:
+#    lib: ../../libraries
+    assets: ../../assets
+widgets     : [mathjax]            # {mathjax, quiz, bootstrap}
+mode        : selfcontained # {standalone, draft}
+---
+
+## What is Shiny?
+
+- Shiny is a platform for creating interactive R programs embeded into a web page.
+- Suppose that you create a prediction algorith, with shiny you can *very easily* create web input form that calls R and thus your prediction algorithm and displays the results.
+- Using Shiny, the time to create simple, yet powerful, web-based interactive data products in R is minimized.
+  - However, it lacks the flexibility of full featured (and more complex) solutions.
+- Shiny is made by the fine folks at R Studio.
+
+---
+## Some mild prerequisites 
+- Shiny doesn't really require it, but as with all web programming, a little knowledge of html, css and js is very helpful
+  - html gives a web page structure and sectioning as well as markup instructions
+  - css gives the style
+  - js for interactivity
+- There are too many tutorials online to count for getting basic proficiency in these topics to count. 
+- Shiny uses [bootstrap](http://getbootstrap.com/) (no relation to the statistics bootstrap) style, which (to me) seems to look nice and renders well on mobile platforms
+
+---
+## What else is out there?
+- Full solutions requiring real knowledge of web client/server programming
+- [OpenCPU](https://public.opencpu.org/) by Jerome Ooms, a really neat project providing an API to call 
+
+---
+## Context
+- You created a novel prediction algorithm to predict risk for developing
+  diabetes.
+    - You're hoping patients and caregivers will be able to enter their data and, if needed, take preventative measures.
+- You want to create a web site so that users can input the relevant predictors and obtain their prediction.
+- Your prediction algorithm (ok, so you're not going to be saving the world with this one)
+  - (link for a real prediction score)[http://www.ncbi.nlm.nih.gov/pubmed/12610029]
+```{r}
+diabetesRisk <- function(glucose){
+  runif(1)
+}
+```
+
+
+---
+## Getting started
+- Make sure you have the latest release of R installed
+- If on windows, make sure that you have Rtools installed
+- `install.packages("shiny")`
+- `libray(shiny)`
+- Great tutorial at 
+[http://rstudio.github.io/shiny/tutorial/](http://rstudio.github.io/shiny/tutorial/)
+- Basically, this lecture is walking through that tutorial offering some of our insights
+- Note, some of the proposed interactive plotting uses of Shiny could be handled by the very simple `manipulate` function [rstudio manipulate](http://www.rstudio.com/ide/docs/advanced/manipulate)
+- Also, `rCharts` is will be covered in a different lecture.
+
+---
+## A Shiny project
+- A shiny project is a directory containing at least two parts
+  - One named ui.R (for user interface) controls how it looks.
+  - One named server.R that controls what it does.
+
+---
+## ui.R
+```
+library(shiny)
+shinyUI(pageWithSidebar(
+  headerPanel("Data science FTW!"),
+  sidebarPanel(
+    h3('Sidebar text')
+  ),
+  mainPanel(
+      h3('Main Panel text')
+  )
+))
+```
+
+---
+## server.r
+```
+library(shiny)
+shinyServer(
+  function(input, output) {
+  }
+)
+```
+
+---
+## To run it
+- In R, change to the directories with these files and type `runApp()`
+- or put the path to the directory as an argument
+- It should open an browser window with the app running
+
+---
+![simplestApp](fig/simplestApp.png "First Shiny app")
+
+
+
+
+
+
+