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Practical Statistics for Data Scientists: 50 Essential Concepts Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce
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“Machine learning tends to be more focused on developing efficient algorithms that scale to large data in order to optimize the predictive model. Statistics generally pays more attention to the probabilistic theory and underlying structure of the model.”
Peter Bruce, Practical Statistics for Data Scientists: 50 Essential Concepts
“Nowhere is the nexus between statistics and data science stronger than in the realm of prediction — specifically the prediction of an outcome (target) variable based on the values of other “predictor” variables.”
Peter Bruce, Practical Statistics for Data Scientists: 50 Essential Concepts
“Moreover, data science (and business in general) is not so worried about statistical significance, but more concerned with optimizing overall effort and results.”
Peter Bruce, Practical Statistics for Data Scientists: 50 Essential Concepts