Welcome to the Data Science Rabbit Podcast, where we dive deep into the mysteries of data science and emerge with newfound knowledge. Join your host Michael Bagalman as we embark on an enlightening journey through the history of the arithmetic mean.

From the insights of ancient Greek philosophers to the mathematical prowess of Indian kings, we'll unravel the historical threads that led to the development of this fundamental statistical tool. Along the way, we'll encounter pivotal figures like Jacob Kobel and Karl Friedrich Gauss, who helped refine our understanding of the mean and its applications.

We'll also delve into the debates surrounding the use of the mean, from Daniel Bernoulli's skepticism to William Stanley Jevons's groundbreaking insights into the nature of measurement and error.

Whether you're a seasoned data scientist or a curious listener eager to learn more about the history of mathematics, join us as we uncover the hidden depths of the arithmetic mean. Subscribe now to the Data Science Rabbit Podcast and join us on this captivating exploration into the heart of statistical reasoning.

Hop down the rabbit hole with your host Michael Bagalman and uncover the tangled roots from whence data science grew!

Journey back to the 60s statistics split that led pioneers like John Tukey to carve an applied path different from the mathematical ivory tower. Learn how the modern phrase "data science" first percolated abroad before reaching American shores. Trace tensions between data modeling and algorithmic camps, with outspoken statisticians like Leo Breiman calling for a paradigm shift. Follow data science’s emergence in tech titans like Google and explosive growth after the famed Netflix competition.

Despite current domination by computer scientists, see openings for statisticians and domain experts to yet claim a seat at the table in this ever-evolving field that extracts practical value from the exponential explosion of data.