Introduction of SPSS Software

Source: Internet
Author: User

Introduction of SPSS statistics statistical analysis software

Well-known statistical analysis software SPSS, now full name for the SPSS Statistics, in order to distinguish from the SPSS company's other products such as SPSS data collection products, SPSS Modeler data Mining products. At the same time, due to the requirements of business analysis applications, SPSS statistics products have been developed into a software system which includes server end and client side, as well as the whole CS architecture. We usually familiar with the SPSS software, it should be said now accurate all called SPSS Statistics Client. IBM in 2009 after the acquisition of SPSS company, now in China's domestic market launch of the latest products, is the IBM SPSS Statistics more than 20 national language version.

SPSS for beginners, skilled and proficient people are more applicable. Provides a complete process of data analysis such as data acquisition, data management and preparation, data analysis, and results reporting, so it covers the entire process of data analysis in a very comprehensive manner, particularly suitable for designing survey plans, statistical analysis of data, and production of related charts in research reports.

In addition, SPSS has a complete data input, editing, statistical analysis, report, graphic production and other functions. Only the SPSS base module provides a method from simple statistical description to complex multifactor statistical analysis. such as the exploratory analysis of data, statistical description, list analysis, two-dimensional correlation, rank correlation, partial correlation, one-element variance analysis, nonparametric test, multivariate regression, survival analysis, covariance analysis, discriminant analysis, factor analysis, Common analysis methods such as cluster analysis.

Introduction of SPSS Modeler software

SPSS Modeler formerly known as Clementine, is an industry-leading data mining platform. The powerful data mining function of SPSS Modeler applies complex statistical methods and machine learning techniques to data, helping customers to uncover patterns and trends hidden in trading systems or enterprise resource planning (ERP), structural databases, and common files.

SPSS Modeler has intuitive operating interface, automated data preparation and mature predictive analysis model, combined with commercial technology can quickly establish a predictive model, and then applied to business activities, to help people improve the decision-making process. Using the predictive insight obtained by SPSS Modeler, the client interacts with the enterprise in real time and realizes the sharing of these insights within the enterprise. Fully support the standard process of data mining crisp-dm. SPSS Modeler can provide data mining related data understanding, data extraction loading transformation, data analysis, modeling, evaluation, deployment and other functions of the whole process.

Introduction of Data Collection

SPSS Company's market research products SPSS data Collection, from a variety of initiatives to listen to your "customer voice" data acquisition system. Collect information by asking potential customers and customers to participate in an online survey, collect feedback from customers through questioning in the day-to-day customer communication in a customer service center or call center, and collect customer attitudes and behavioral information manually while the customer is shopping in the store. SPSS Data Collection can get all the feedback in the center based on web, telephone, off-line and so on.

Iv. introduction of SPSS C&ds software

Provides an enterprise-class analysis Asset Center repository. The aim is to provide the unified management and deployment of SPSS Statistics, SPSS Modeler, SAS and other product analysis results. At the same time, promote the cooperation of the Organization analyst, make the release of the analysis result quicker and more effective; Automate the analysis process, improve the consistency and controllability of the analysis results, and automatically distribute the analysis results to relevant people and systems to support enterprise decision making in a wider range of business areas.

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