Think StatsIf 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.

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acomputer scientist trying to optimize system performance collected data on the time in microseconds between requests for a particular process service.
2,808 4,201 3,848 9,112 2,082 5,913 1,620 6,719 21,657
3,072 2,949 11,768 4,731 14,211 1,583 9,853 78,811 6,655
1,803 7,012 1,892 4,227 6,583 15,147 4,740 8,528 10,563
43,003 16,723 2,613 26,463 34,867 4,191 4,030 2,472 28,840
24,487 14,001 15,241 1,643 5,732 5,419 28,608 2,487 995
3,116 29,508 11,440 28,336 3,440
Contents
Chapter 1 Statistical Thinking for Programmers  1 
Chapter 2 Descriptive Statistics  11 
Chapter 3 Cumulative Distribution Functions  23 
Chapter 4 Continuous Distributions  33 
Chapter 5 Probability  47 
Chapter 6 Operations on Distributions  61 