Language:Chinese.Pub. Date:2016-09-01 Pages:322 Publisher: Paperback Machinery Industry Press. combined with the reality of the marketing problems revealed in the market research and analysis how to use R. The main contents include: R review. data description. the relationship between continuous variables. form and visualization. statistical test. linear model. how to reduce the complexity. confirmatory factor analysis.

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Title: R language market research and analysis(Chinese Edition)
ISBN 10: 7111549902
ISBN 13: 9787111549901
Binding: paperback
Condition: New

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Synopsis

本书结合现实中的市场营销问题揭示了在市场研究分析中如何使用R。主要内容包含:R综述，数据描述，连续变量之间的关系，表格和可视化，统计检验，线性模型，如何降低复杂度，验证性因子分析和结构方程模型，聚类和判别，购物篮分析，模型选择等。中文版序译者序前言第一部分R语言基础知识第1章欢迎使用R21.1R是什么21.2为什么用R21.3为什么不用R31.4什么时候用R41.5如何使用本书41.6关键点6第2章R综述72.1开始72.2R用途快速指南82.3R命令基础112.4基础对象122.5数据框212.6载入和存储数据242.7编写函数*272.8清理302.9知识拓展*302.10关键点31第二部分数据分析基础知识第3章数据描述343.1模拟数据343.2关于变量的函数383.3概括数据框413.4单变量可视化453.5知识拓展*543.6关键点55第4章连续变量之间的关系564.1零售数据564.2用散点图探索变量间关系604.3把多张图合并为一张图654.4散点图矩阵674.5相关系数704.6探索问卷调查回复间的相关性*764.7知识拓展*784.8关键点78第5章组比较：表格和可视化805.1模拟客户分组数据805.2各组对应的描述统计量875.3知识拓展*965.4关键点97第6章组比较：统计检验986.1用于比较的数据986.2频数检验：chisq.test()986.3观测比例检验：binom.test()1016.4组均值检验：t.test()1036.5多组均值检验：ANOVA1046.6初识贝叶斯ANOVA*1096.7知识拓展*1136.8关键点114第7章识别结果变量的驱动因子：线性模型1157.1游乐场数据1157.2用lm()函数拟合线性模型1177.3拟合多元线性模型1257.4因子自变量1297.5交互效应1317.6避免过度拟合1347.7建议的线性模型拟合过程1347.8贝叶斯线性模型：MCMCregress()*1357.9知识拓展*1367.10关键点137第三部分高级营销应用第8章降低数据复杂度1408.1消费者品牌评分数据1408.2主成分分析和感知图1448.3探索性因子分析1518.4高维标度化简介1578.5知识扩展*1608.6关键点160第9章线性模型相关的其他话题1629.1处理高度相关的变量1629.2二项结果变量的线性模型：逻辑回归1669.3分层线性模型1759.4贝叶斯分层线性模型*1829.5频率学派和贝叶斯学派HLM模型的简单比较*1879.6知识拓展*1909.7关键点191第10章验证性因子分析和结构方程模型19310.1结构模型的出发点19310.2量级评估：CFA19510.3更一般的模型：结构方程模型20410.4PLS模型20910.5知识拓展*21510.6关键点216第11章客户分组：聚类和判别21711.1客户分组的思想21711.2客户分组数据21911.3聚类21911.4判别分析23411.5预测：识别潜在客户*24211.6知识拓展*24411.7关键点245第12章关联法则：购物篮分析24712.1基础关联法则24712.2零

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