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SPSS Statistical Analysis (44) Basis of Clustering and Discriminant Analysis
SPSS
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人們認識某類事物時往往會先對這類事物的各個對象進行分析，以便尋找同類事物的各種特徵。如在國民經濟領域，有時需要根據各省份的經濟特點、產業結構、生產總值、人口數量、人均收入、消費特點等分成幾個集合。比如分成經濟發達區域和經濟不發達區域，資源豐富地區和資源匱乏地區等。分成這樣的一些地區之後，屬於同一類型的區域，國家可以採用相似的經濟政策。
When people recognize a certain kind of things, they often analyze the various objects of this kind of things first in order to find various characteristics of the same kind of things. For example, in the field of national economy, it is sometimes necessary to divide into several sets according to the economic characteristics, industrial structure, GDP, population, per capita income and consumption characteristics of each province. For example, it is divided into economically developed regions and economically underdeveloped regions, resource-rich regions and resource-poor regions. After being divided into such regions, countries can adopt similar economic policies for regions of the same type.
而統計學研究這類問題的主要方法是聚類分析和判別分析。顧名思義，聚類分析的主要思想是認為研究的樣本或指標之間具有不同程度的相似性（親疏關係）。根據這種相似性，把一些相似程度較大的樣本聚合為一類，把另一些彼此之間相似程度較大的樣本又聚合為另一類，形成一個由小到大的分類系統。最後將整個分類系統畫成一張譜系圖。
The main methods of statistical research on such problems are cluster analysis and discriminant analysis. As the name implies, the main idea of cluster analysis is that the samples or indicators studied have different degrees of similarity (intimacy). According to this similarity, some samples with greater similarity are aggregated into one category, and other samples with greater similarity are aggregated into another category, forming a classification system from small to large. Finally, draw a pedigree of the whole classification system.
判別分析是判別樣本所屬類型的一種統計方法，和聚類分析一樣，判別分析也用來解決各種分類問題，不同的是，判別分析在已知研究對象分為若干類型並已取得各種類型的一批已知樣本的觀測量數據的基礎上，根據某種準則建立判別式，然後對未知類型的樣本進行判別分析。判別準則主要有距離判別、Bayes判別和Fisher判別等。
Discriminant analysis is a statistical method to determine the type of samples. Like cluster analysis, discriminant analysis is also used to solve various classification problems. The difference is that discriminant analysis establishes a discriminant according to certain criteria on the basis of the known research objects divided into several types and the observed data of a batch of known samples of various types, and then carries out discriminant analysis on samples of unknown types. The discriminant criteria mainly include distance discriminant, Bayes discriminant and Fisher discriminant.
下期預告：本期，我們學習了
聚類分析和判別分析的基礎知識。
下一期，我們將會學習
二階聚類的理論和實例操作。
Preview for next issue: In this issue, we learned the basic knowledge of cluster analysis and discriminant analysis. In the next issue, we will learn the theory and example operation of second-order clustering.
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That's all for today's sharing. If you have unique ideas about today's article, please leave us a message. Let's meet tomorrow. I wish you a happy day today!
參考資料：百度百科，《SPSS 23 統計分析實用教程》
翻譯：百度翻譯
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