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商品描述
Praise for Linear Models with R:
This book is a must-have tool for anyone interested in understanding and applying linear models. The logical ordering of the chapters is well thought out and portrays Faraway's wealth of experience in teaching and using linear models. ... It lays down the material in a logical and intricate manner and makes linear modeling appealing to researchers from virtually all fields of study. -Biometrical Journal
Throughout, it gives plenty of insight ... with comments that even the seasoned practitioner will appreciate. Interspersed with R code and the output that it produces one can find many little gems of what I think is sound statistical advice, well epitomized with the examples chosen...I read it with delight and think that the same will be true with anyone who is engaged in the use or teaching of linear models. -Journal of the Royal Statistical Society
Like its widely praised, best-selling companion version, Linear Models with R, this book replaces R with Python to seamlessly give a coherent exposition of the practice of linear modeling. Linear Models with Python offers up-to-date insight on essential data analysis topics, from estimation, inference and prediction to missing data, factorial models and block designs. Numerous examples illustrate how to apply the different methods using Python.
Features:
- Python is a powerful, open source programming language increasingly being used in data science, machine learning and computer science. Python and R are similar, but R was designed for statistics, while Python is multi-talented.
- This version replaces R with Python to make it accessible to a greater number of users outside of statistics, including those from Machine Learning.
- A reader coming to this book from an ML background will learn new statistical perspectives on learning from data.
- Topics include Model Selection, Shrinkage, Experiments with Blocks and Missing Data.
- Includes an Appendix on Python for beginners.
Linear Models with Python explains how to use linear models in physical science, engineering, social science and business applications. It is ideal as a textbook for linear models or linear regression courses.
商品描述(中文翻譯)
對於 使用 R 的線性模型:
這本書是任何有興趣理解和應用線性模型的人的必備工具。章節的邏輯排序經過深思熟慮,展現了 Faraway 在教學和使用線性模型方面的豐富經驗。... 它以邏輯且複雜的方式呈現材料,並使線性建模對幾乎所有研究領域的研究人員都具有吸引力。 - 生物統計學期刊
整本書提供了大量的見解... 其評論即使是經驗豐富的從業者也會欣賞。書中穿插了 R 代碼及其產生的輸出,讀者可以找到許多我認為是合理的統計建議的小寶石,這些建議在所選的例子中得到了很好的體現... 我愉快地閱讀了這本書,並認為任何從事線性模型使用或教學的人都會有同樣的感受。- 皇家統計學會期刊
與其廣受讚譽的暢銷伴侶版本 使用 R 的線性模型 相比,這本書將 R 替換為 Python,無縫地提供了線性建模實踐的連貫闡述。使用 Python 的線性模型提供了有關基本數據分析主題的最新見解,從估計、推斷和預測到缺失數據、因子模型和區塊設計。許多例子說明了如何使用 Python 應用不同的方法。
特色:
- Python 是一種強大且開源的程式語言,越來越多地應用於數據科學、機器學習和計算機科學。Python 和 R 相似,但 R 是為統計而設計的,而 Python 則是多才多藝的。
- 這個版本用 Python 替代 R,使其對統計以外的更多用戶可及,包括來自機器學習領域的人。
- 來自機器學習背景的讀者將學習到從數據中學習的新統計觀點。
- 主題包括模型選擇、收縮、區塊實驗和缺失數據。
- 包括一個針對初學者的 Python 附錄。
使用 Python 的線性模型解釋了如何在物理科學、工程、社會科學和商業應用中使用線性模型。它非常適合作為線性模型或線性回歸課程的教科書。
作者簡介
Julian J. Faraway is a professor of statistics in the Department of Mathematical Sciences at the University of Bath. His research focuses on the analysis of functional and shape data with particular application to the modeling of human motion. He earned a PhD in statistics from the University of California, Berkeley.
作者簡介(中文翻譯)
Julian J. Faraway 是巴斯大學數學科學系的統計學教授。他的研究專注於功能數據和形狀數據的分析,特別應用於人類運動的建模。他在加州大學伯克利分校獲得統計學博士學位。