Distribution of Sample Means

This shiny pitch is intended to illustrate the Central Limit Thoerem (CLT) in Coursera's Developing Data Products module.

My approach to App creation:

The central limit theorem states that the distribution of the sum (or average) of a large number of independent, identically distributed variables will be approximately normal, regardless of the underlying distribution.

• Building on this idea I have considered many different types
  • Normal
  • Uniform
  • Log-normal
  • Espontential

My Shiny app can be found here:

https://dskswu.shinyapps.io/Distribution/

My GitHub reprository can be found here:

https://github.com/williamrgre/Shiny-Application-Presentation

library(ggplot2)
set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), 
                   rating = c(rnorm(200),rnorm(200, mean=.8)))
# View first few rows
head(dat)

  cond     rating
1    A -1.2070657
2    A  0.2774292
3    A  1.0844412
4    A -2.3456977
5    A  0.4291247
6    A  0.5060559