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SAS System for Regression (Third Edition) (Wiley Series in Probability and Statistics) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

SAS System for Regression (Third Edition) (Wiley Series in Probability and Statistics)
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简体网页||繁体网页
Rudolf J. Freund; Ramon C. Littell 作者
SAS Publishing
译者
2000-10-17 出版日期
264 页数
USD 43.95 价格
Paperback
丛书系列
9781580257251 图书编码

SAS System for Regression (Third Edition) (Wiley Series in Probability and Statistics) 在线电子书 图书标签: SAS   

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SAS System for Regression (Third Edition) (Wiley Series in Probability and Statistics) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

SAS System for Regression (Third Edition) (Wiley Series in Probability and Statistics) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

SAS System for Regression (Third Edition) (Wiley Series in Probability and Statistics) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


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SAS System for Regression (Third Edition) (Wiley Series in Probability and Statistics) 在线电子书 图书描述

Learn to perform a wide variety of regression analyses using SAS software with this example-driven revised favorite from SAS Publishing. With this third edition you will learn the basics of performing regression analyses using a wide variety of models including nonlinear models. Other topics include performing linear regression analyses using PROC REG and diagnosing and providing remedies for data problems, including outliers and multicollinearity. Examples feature numerous SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others. A helpful discussion of theory is supplied where necessary. Some knowledge of both regression and SAS are assumed. The updated third edition includes revisions, updated material, and new material. You'll find information on using SAS/INSIGHT software, regression with a binary response with emphasis on PROC LOGISTIC, and nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, data sets by the OUTEST option described and illustrated, and using PROC SCORE to predict another data set.

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