求助：请问SPSS能做二次正交旋转组合设计数据分析吗？

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求助：请问SPSS能做二次正交旋转组合设计数据分析吗？小弟是新手，麻烦大虾们给讲解一下吧，或者是有这种方面的教材也行。谢谢了。

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关键词：SPSS 数据分析 组合设计 PSS 数据 SPSS 正交 组合设计 数据分析专题 数据处理 数据分析软件 数据分析报告 面板数据分析 excel数据分析 数据分析方法 项目数据分析

怎么只有浏览的，每人回复呀？是不是这问题太幼稚了亚？

是太专业了。呵呵

帮顶啊，最近我也在纠结这个，

统计知识都是  碎片，根本连不上，还请会的大神给解释解释。SAS  做回归也行

In factor analysis, which is a method of reducing a large number of variables into a smaller number of "factors," different methods of "rotation" can be used to find patterns in data. Each carries different assumptions about the data. So choosing the correct method of rotation is crucial to making the data easier to understand. Have a question? Get an answer from online tech support now!
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How to Read Factor Analysis How to Use Factor Analysis

Orthogonal Rotation
In an orthogonal rotation, the factors produced are uncorrelated, which makes the solutions it produces easier to interpret. In the July 2005 issue of "Practical Assessment, Research and Evaluation," Anna B. Costello and Jason W. Osborne reported that orthogonal rotation was used in more than half of the studies in a survey of the PsycINFO database. This is possibly because orthogonal is the default setting in most statistical analysis programs, but it is often not the most appropriate method.

Variables in a factor analysis are usually connected in some way. In the social sciences, for example, correlation among factors would be expected because researchers rarely study large numbers of completely independent aspects of human behavior at the same time. If the variables are correlated, oblique rotation should be used instead.

The three commonly used forms of orthogonal rotation are varimax, quartimax and equamax.

Varimax Rotation
Varimax rotation is the most commonly used method of orthogonal rotation. It maximizes the variance of factors across the variables, which produces a simpler solution. This is the default setting in most statistical programs, such as Statistical Package for the Social Sciences (SPSS) and Statistical Analysis Systems (SAS).



Read more : http://www.ehow.com/list_7450638_factor-analysis-rotation-methods.html

Application of Quadratic Rotation-Orthogonal Composite Experimental Design to Assess the Relationship between Growth Environment and Ultraweak Luminescence of Mint

Yao Zhan, Yi Lin, Chunfang Wang, Jianping Li, Yong Yu

Abstract
Quadratic rotation-orthogonal composite experimental design was applied in this experiment to obtain the ultraweak luminescence property of mint affected by multilateral growth environmental factors including illumination, temperature, humidity, and moisture. The influence models of four factors on luminescence were established. Analysis showed that different factors and their interactions had different effect on luminous value, among which the interaction of illumination and humidity had the most significant influence on luminescence of mint (p ≤ 0.01). And the maximum luminous value was obtained when ten stick of lamp tube (intensity of illumination value 4229 Lx) was used, mean temperature, humidity and water were 35 ℃, 85% and 90 mL/d respectively. On the base of that, linear effects and their interactions that affected ultraweak luminescence were also studied.
http://link.springer.com/chapter/10.1007/978-3-642-36137-1_14

不知道，菜鸟报到

能做的，有书说明是SPSS12.0 for windows 在农业统计中的应用

SPSS多因素方差分析里做  设置非饱和模型，在交互分析里选择二次正交设计。