Computer Age Statistical Inference : Algorithms, Evidence, and Data Science (Hardocver)

Bradley Efron, Trevor Hastie

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商品描述

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

商品描述(中文翻譯)

二十一世紀見證了統計方法的驚人擴展,無論在範圍還是影響力上都是如此。"大數據"、"數據科學"和"機器學習"已成為新聞中熟悉的詞彙,因為統計方法被應用於現代科學和商業的龐大數據集。我們是如何到達這裡的?我們又將走向何方?本書帶領我們穿越自1950年代電子計算機引入後的數據分析革命。從古典推論理論(貝葉斯、頻率論、費雪)開始,各章節探討了一系列有影響力的主題:生存分析、邏輯回歸、經驗貝葉斯、劍橋樣本和自助法、隨機森林、神經網絡、馬爾可夫鏈蒙特卡羅、模型選擇後的推論等等。這種独特的現代方法將方法論和算法與統計推論相結合。本書以對統計和數據科學未來方向的推測作為結尾。