Coursera-Statistical-Inference-Project The project consists of two parts:
A simulation exercise. Basic inferential data analysis. You will create a report to answer the questions. Given the nature of the series, ideally you'll use knitr to create the reports and convert to a pdf. However, feel free to use whatever software that you would like to create your pdf. Each pdf report should be no more than 3 pages with 3 pages of supporting appendix material if needed (code, figures, etcetera).
####Project Instructions, part One
In this project you will investigate the exponential distribution in R and compare it with the Central Limit Theorem. The exponential distribution can be simulated in R with rexp(n, lambda) where lambda is the rate parameter. The mean of exponential distribution is 1/lambda and the standard deviation is also 1/lambda.
Set lambda = 0.2 for all of the simulations.
You will investigate the distribution of averages of 40 exponentials. Note that you will need to do a thousand simulations.
Illustrate via simulation and associated explanatory text the properties of the distribution of the mean of 40 exponentials. You should:
Show the sample mean and compare it to the theoretical mean of the distribution.
Show how variable the sample is (via variance) and compare it to the theoretical variance of the distribution.
Show that the distribution is approximately normal.
####Project Instructions, part Two
Load the ToothGrowth data and perform some basic exploratory data analyses
Provide a basic summary of the data
Use confidence intervals and/or hypothesis tests to compare tooth growth by supp and dose. (Only use the techniques from class, even if there's other approaches worth considering)
State your conclusions and the assumptions needed for your conclusions.