Cooking Up Statistics: The Science & The Art By Letisha Smith Abstract: After adopting the New Year's Resolution to be healthier, I immediately recognized a common flaw with recommended meal plans. Daily dishes often contain their own set of ingredients that are rarely reused and consequently go to waste. Traditionally, this problem has been solved by finding recipes that use leftover ingredients. However, this approach is reactive, not proactive. Therefore, I began to ponder if machine learning could be used to optimize meal prep. In this talk, I will share lessons learned while using R to maximize the number of meals made with a minimal amount of ingredients. Bio: Letisha Smith recently graduated with her Master’s in Applied Statistics from New York University. She currently works as a Data Scientist at Teachers Pay Teachers. In 2018, the Royal Statistical Society recognized her with the Award for Statistical Excellence in Early Career Writing. Twitter: @letishaaudrey Presented at the 2019 New York R Conference (May 11th, 2019)