How many machines will we need for Q4? How big should our next datacenter build be? What are the odds this project will be completed on time? What does a network packet loss rate of 1% mean for my application?
Do you feel like you ought to have a working knowledge of statistics, but don’t know where to begin? If you took a statistics class in college, but have forgotten most of it, or you’ve never had any formal training in statistics, this class is for you. My goal is to give you a basic toolset to begin reasoning statistically through a series of interactive examples.
We’ll do an exercise in estimation, where you’ll learn how well calibrated you are as an estimator. We’ll use the data we get from the estimation exercise to explore one of the most useful ideas in statistics: the binomial distribution. We’ll conduct a key statistical test, the chi-square test, which use can to tell if the data you’re observing match what you’d expect or if the pattern is different. And last, we’ll solve a problem in decision theory and along the way learn about the normal distribution.
Though I’ll use a little bit of scary looking math, you should still attend if you’ve forgotten all the math you learned in school. I show how to use software like excel and sage to do all the mathematical heavy lifting.
John has been extracting value from large datasets for over 20 years at hedge funds, small data-driven startups, Amazon, and now Pinterest. He has deep experience in machine learning, data visualization, on-line experimentation, website performance and real-time fault analysis. An empiricist at heart, “Just do the experiment!” is his favorite call to arms.
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