Think Stats
If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts. Develop your understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Learn topics not usually covered in an introductory course, such as Bayesian estimation Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data
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It's a textbook. A good one. I didn't finish it. Wiping the slate clean! I saw Allen Downey give a talk on Bayesian stats, and it was fun and informative. I think he's great.
One annoyance. I think I'm maybe the perfect audience for this book: someone who took stats long ago, has worked with data ever since in some capacity, but has moved further and further away from the first principles/fundamentals. Someone who speaks Python and wants to port all of her Stata skillz onto pandas (the Python library, not the Chinese bear - okay, also the Chinese bear). So, in a way, this book was perfect for that. MY ONE COMPLAINT is that Allen provides many helper functions and .py files pre-written for you to play around with. I would have preferred less hand-holding, and more: Now build a function that will give you the cumulative distribution function! But then: who am I to complain. I didn't finish it (for now). And it can be hard, sometimes, to find the perfect puzzle piece for your current skillset/desires/time constraint on the Great Learning Journey that is life. images of pandas feverishly computing z-scores, while I cackle above them, “Work harder!!! Why are you so slow!!!” images of furry paws clutching pens and notebooks, scribbling
