• Use various distributions and corresponding parameters to create random samples
• Plot random samples to check if they look like Normal distribution

Read an article about this simulation at

• https://www.r-bloggers.com
  
• Simulation

Link to the CLT app
Link to the Github repo

Links to:
1. ui.R file
2. server.R file
3. README.md file

• Sample size – Slider input
• Distributions and parameters as inputs
• Click on "Sample now" to draw a random sample

4 plots will be drawn only after clicking on "Sample now"

1. Distribution of one random sample
   
2. Sampling distribution of the sum
   
3. Sampling distribution of the mean
   
4. Sampling distribution of the variance

Next slide provides details of the statistical distributions

1. Exponential: Mean
2. Normal: Mean and SD
3. Uniform: Min and Max
4. Poisson: Lambda
5. Cauchy: Location and scale
6. Binomial: Size and Success probability
7. Gamma: Shape and scale
8. Chi square: DF and ncp
9. Student t: DF

Above distributions assymptotically follow normal distribution as the sample size increases