Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples-not to perform entire analyses.After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference.Focusing on the assumptions that underlie popular statistical methods, this textbook explains how and why these methods are used to analyze experimental data.
具体描述
读后感
评分
评分
评分
评分
用户评价
例子蛮多的，理论降低到最小化。特别适合考试，但没什么实用价值感觉。
评分例子蛮多的，理论降低到最小化。特别适合考试，但没什么实用价值感觉。
评分例子蛮多的，理论降低到最小化。特别适合考试，但没什么实用价值感觉。
评分例子蛮多的，理论降低到最小化。特别适合考试，但没什么实用价值感觉。
评分例子蛮多的，理论降低到最小化。特别适合考试，但没什么实用价值感觉。
相关图书
本站所有内容均为互联网搜索引擎提供的公开搜索信息，本站不存储任何数据与内容，任何内容与数据均与本站无关，如有需要请联系相关搜索引擎包括但不限于百度，google,bing,sogou 等
© 2025 book.quotespace.org All Rights Reserved. 小美书屋 版权所有