What is the probability that in a box of a dozen donuts picked from 14 flavors there’s no more than 3 flavors in the box?

Problem

Dave’s Donuts offers 14 flavors of donuts (consider the supply of each flavor as being unlimited). The “grab bag” box consists of flavors randomly selected to be in the box, each flavor equally likely for each one of the dozen donuts. What is the probability that at most three flavors are in the grab bag box of a dozen?

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Time Series and MCHT

Introduction

Over the past few weeks I’ve published articles about my new package, MCHT, starting with an introduction, a further technical discussion, demonstrating maximized Monte Carlo (MMC) hypothesis testing, bootstrap hypothesis testing, and last week I showed how to handle multi-sample and multivariate data. This is the final article where I explain the capabilities of the package. I show how MCHT can handle time series data.

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Bootstrap Testing with MCHT

Introduction

Now that we’ve seen MCHT basics, how to make MCHTest() objects self-contained, and maximized Monte Carlo (MMC) testing with MCHT, let’s now talk about bootstrap testing. Not much is different when we’re doing bootstrap testing; the main difference is that the replicates used to generate test statistics depend on the data we feed to the test, and thus are not completely independent of it. You can read more about bootstrap testing in [1].

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Announcing MCHT: An R Package for Bootstrap and Monte Carlo Hypothesis Testing

I am very excited to announce my first (public) package (and the second package I’ve ever written, the first being unannounced until the accompanying paper is accepted). That package is MCHT, a package for bootstrap and Monte Carlo hypothesis testing, currently available on GitHub.

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