Applied Univariate, Bivariate, and Multivariate Statistics Using Python: A Beginner's Guide to Advanced Data Analysis (使用 Python 的應用單變量、雙變量及多變量統計：進階數據分析的初學者指南)

Denis, Daniel J.

Applied Univariate, Bivariate, and Multivariate Statistics Using Python: A Beginner's Guide to Advanced Data Analysis

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商品描述

A practical, "how-to" reference for anyone performing essential statistical analyses and data management tasks in Python

Applied Univariate, Bivariate, and Multivariate Statistics Using Python delivers a comprehensive introduction to a wide range of statistical methods performed using Python in a single, one-stop reference. The book contains user-friendly guidance and instructions on using Python to run a variety of statistical procedures without getting bogged down in unnecessary theory. Throughout, the author emphasizes a set of computational tools used in the discovery of empirical patterns, as well as several popular statistical analyses and data management tasks that can be immediately applied.

The datasets used in the book are small enough to easily be entered into Python manually, although they can also be downloaded for free from www.datapsyc.com. Only minimal knowledge of statistics is assumed, and the book is perfect for those seeking an easily accessible toolkit for statistical analysis with Python. Applied Univariate, Bivariate, and Multivariate Statistics Using Python represents the fastest way to learn how to analyze data with Python.
Readers will also benefit from the inclusion of:

  • A thorough review of essential statistical principles, including types of data, scales of measurement, significance tests, significance levels, and type I and type II errors
  • An introduction to Python, including how to communicate with Python
  • A treatment of exploratory data analysis, basic statistics, and visual displays, including frequencies and descriptives, stem-and-leaf plots, q-q plots, box-and-whisker plots, and data transformations
  • An exploration of data management in Python

Perfect for undergraduate and graduate students in the social, behavioral, and natural sciences, Applied Univariate, Bivariate, and Multivariate Statistics Using Python will also earn a place in the libraries of researchers and data analysts seeking a quick go-to resource for univariate, bivariate, and multivariate analysis in Python.

商品描述(中文翻譯)

一本實用的「如何做」參考書，適合任何在 Python 中執行基本統計分析和數據管理任務的人。《Applied Univariate, Bivariate, and Multivariate Statistics Using Python》提供了對各種使用 Python 執行的統計方法的全面介紹，成為一本一站式的參考書。該書包含了使用 Python 執行各種統計程序的使用者友好指導和說明，並不會陷入不必要的理論中。全書中，作者強調了一組用於發現經驗模式的計算工具，以及幾種可以立即應用的流行統計分析和數據管理任務。

書中使用的數據集足夠小，可以輕鬆手動輸入到 Python 中，雖然也可以從 www.datapsyc.com 免費下載。書中假設讀者對統計學的知識僅需最基本的了解，對於尋求易於使用的 Python 統計分析工具包的人來說，這本書是完美的選擇。《Applied Univariate, Bivariate, and Multivariate Statistics Using Python》代表了學習如何用 Python 分析數據的最快方式。

讀者還將受益於以下內容的包含：
- 對基本統計原則的徹底回顧，包括數據類型、測量尺度、顯著性檢驗、顯著性水平，以及第一型和第二型錯誤
- Python 的介紹，包括如何與 Python 進行交流
- 對探索性數據分析、基本統計和視覺顯示的處理，包括頻率和描述性統計、莖葉圖、Q-Q 圖、箱形圖和數據轉換
- 在 Python 中進行數據管理的探索

這本書非常適合社會科學、行為科學和自然科學的本科生和研究生，也將成為研究人員和數據分析師尋求快速參考資源的圖書館中的一部分，特別是在 Python 中進行單變量、雙變量和多變量分析的資源。

作者簡介

Daniel J. Denis, PhD, is Professor of Quantitative Psychology at the University of Montana. He is the author of Applied Univariate, Bivariate, and Multivariate Statistics and Applied Univariate, Bivariate, and Multivariate Statistics Using R.

作者簡介(中文翻譯)

丹尼爾·J·丹尼斯（Daniel J. Denis），博士，是蒙大拿大學的定量心理學教授。他是《應用單變量、雙變量和多變量統計》（Applied Univariate, Bivariate, and Multivariate Statistics）以及《使用 R 的應用單變量、雙變量和多變量統計》（Applied Univariate, Bivariate, and Multivariate Statistics Using R）的作者。

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