Simpsons_Paradox_usingshiny.Rmd

---
title: "Explain Simpson's Paradox"
author: "Sandeep Anand"
date: "June 20, 2017"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# TITLE: Using Shiny To Explain Simpson's Paradox

## Link to the App: https://sananand007.shinyapps.io/simpsonsparadox/

### What is Simpson's Paradox

Every Simpson's paradox involves at least three variables:

+ the explained
+ the observed explanatory
+ the lurking explanatory
  If the effect of the observed explanatory variable on the explained variable changes directions when you account for the lurking explanatory variable, you've got a Simpson's         Paradox.
    

### Effect that is shown here uses the concept of Bias seen during Admissions at the University of California , Berkley in 1973 

In 1973, the University of California-Berkeley was sued for sex discrimination. The numbers looked pretty incriminating: the graduate schools had just accepted 44% of male applicants but only 35% of female applicants. But By Properly Pooling the admissions , by breaking them down into each department , it was seen that The trend was reversed in some cases . 


## User Knowledge To be Noted / Notes

The Explaination and the representation is Trivial and novice approach, and used very simple Widgets to explain the effect of Simpson's Paradox . 
  
*I will be trying to improve on this effort with more verions in the future*

- Use of Two Slider inputs , which gives inputs to the graphs 
  + The top Slider being for the input to the easy department 
  + The bottom Slider being the input to the difficult department
  + There are two Graphs on the top Row, that are reactive to the input sliders 
    + The left bar graph represents the change % of Male and Female admits in the easy department with variance of the easy department input slider
    + The right bar graph represents the change % of Male and Female admits in the Hard department with variance of the Hard department input slider
  + The final Bar graph in Green that is the combined bar plot, we see that , the combined plot varies as such: 
    - **If % Male admitted (easy/Hard) > % Male admitted (easy/Hard) then % Male admitited [Combined (easy+Hard)] can be less than % FeMale admitited [Combined (easy+Hard)]**
    - **If % Male admitted (easy/Hard) < % Male admitted (easy/Hard) then % Male admitited [Combined (easy+Hard)] can be greater than % FeMale admitited [Combined (easy+Hard)]**