| Industrial upgrade and social progress are principally promoted by rapid development of high-tech industry, which attaches great importance to the world’s major countries as well as China. Statistics, analysis, making decision and deployment of high-tech industry is a research field which governments and researchers are highly concerned.Previous Statistical Research on high-tech industries are emphasized on the traditional model analysis and theory, and only conducted a few spatial analysis of single indicators, meanwhile traditional analysis models are combined with spatial correlation analysis and use of information systems to enhance the performance, which are seldom researched.Spatial auto-correlation analysis has an important position in spatial statistics method, two classical methods(Moran’I and Geary Ratio C) are widely implied in spatial in spatial statistics; comprehensive evaluation, analytic hierarchy process and principal component analysis methods are classified in statistical analysis. It is expected to make an empirical study for high-tech industry development data in China with the combination of the traditional statistics models and spatial statistics models, which get deeper data analysis. Studies show that the spatial correlation model combined with the traditional statistics model were effective for data treating; whereas global correlation is not strong enough, and local areas exists certain correlation in China’s high-tech industrial development.Comprehensive evaluation and analysis system is an important tool to deal with data, improve research speed and efficiency. "statistical analysis and comprehensive evaluation system" is successfully developed by boom statistical R language as the core, and the research demonstrates that statistical analysis model can succeed in the information processing and spatial map processing, and becomes an important tool and platform for statisticians.
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