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Put statistics into practice with Python! Data-driven decisions rely on statistics. Statistics Every Programmer Needs introduces the statistical and quantitative methods that will help you go beyond "gut feeling" for tasks like predicting stock prices or assessing quality control, with examples using the rich tools of the Python data ecosystem. Statistics Every Programmer Needs will teach you how to: Apply foundational and advanced statistical techniques Build predictive models and simulations Optimize decisions under constraints Interpret and validate results with statistical rigor Implement quantitative methods using Python You've got the raw data—how do you turn it into actionable insights you can use to make decisions? Statistics and quantitative technologies are the essential tools every programmer needs for navigating uncertainty, optimizing outcomes, and making informed choices. In this hands-on guide, stats expert Gary Sutton blends the theory behind these statistical techniques with practical Python-based applications, offering structured, reproducible, and defensible methods for tackling complex decisions.
Put statistics into practice with Python!
Data-driven decisions rely on statistics. Statistics Every Programmer Needs introduces the statistical and quantitative methods that will help you go beyond "gut feeling" for tasks like predicting stock prices or assessing quality control, with examples using the rich tools of the Python data ecosystem.
Statistics Every Programmer Needs will teach you how to:
Apply foundational and advanced statistical techniques
Build predictive models and simulations
Optimize decisions under constraints
Interpret and validate results with statistical rigor
Implement quantitative methods using Python
You've got the raw data—how do you turn it into actionable insights you can use to make decisions? Statistics and quantitative technologies are the essential tools every programmer needs for navigating uncertainty, optimizing outcomes, and making informed choices. In this hands-on guide, stats expert Gary Sutton blends the theory behind these statistical techniques with practical Python-based applications, offering structured, reproducible, and defensible methods for tackling complex decisions.