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Coursera-Statistical-Inference-Project

The project consists of two parts:

  1. A simulation exercise.
  2. 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.

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