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SAS (Computer program language)
概要
作品:
19 作品在 14 項出版品 14 種語言
書目資訊
Regression modeling :methods, theory, and computation with SAS /
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(書目-語言資料,印刷品)
SAS and R :data management, statistical analysis, and graphics /
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(書目-語言資料,印刷品)
Using SAS for data management, statistical analysis, and graphics /
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(書目-語言資料,印刷品)
R for SAS and SPSS users
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(書目-電子資源)
SAS and Rdata management, statistical analysis, and graphics /
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(書目-電子資源)
Regression modelingmethods, theory, and computation with SAS /
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(書目-電子資源)
Practical business analytics using SASa hands-on guide /
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(書目-電子資源)
SAS programming and data visualization techniquesa power user's guide /
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(書目-電子資源)
Statistical hypothesis testing with SAS and R /
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(書目-語言資料,印刷品)
Learn business analytics in six steps using SAS and Ra practical, step-by-step guide to learning business analytics /
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(書目-電子資源)
Handbook of SAS® DATA Step programming
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(書目-電子資源)
Statistical data analysis using SASintermediate statistical methods /
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(書目-電子資源)
Applying predictive analyticsfinding value in data /
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(書目-電子資源)
SAS stored processesa practical guide to developing web applications /
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(書目-電子資源)
Learn data science using SAS Studioa quick-start guide /
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(書目-電子資源)
Microsimulation population projections with SASa reference guide /
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(書目-電子資源)
SAS for R usersa book for budding data scientists /
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(書目-電子資源)
Applying predictive analyticsfinding value in data /
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(書目-電子資源)
Supervised machine learningoptimization framework and applications with SAS and R /
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(書目-電子資源)
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Information visualization.
Communications Engineering, Networks.
Statistical matching.
Psychological Methods/Evaluation.
Probability Theory and Stochastic Processes.
Computer Graphics.
Programming Techniques.
Database Management.
Business
Statistical Theory and Methods.
Plant Sciences.
Data mining.
Demography.
SAS (Computer program language)
R (Computer program language)
Supervised learning (Machine learning)
Database management.
Data Mining and Knowledge Discovery.
Big Data.
Computational Intelligence.
Demography
Mathematical statistics
Statistical hypothesis testing.
Web applications.
Big data.
Regression analysis
Statistics.
Statistics and Computing/Statistics Programs.
Probability and Statistics in Computer Science.
Methodology of the Social Sciences.
Computer Science.
Mathematical Software.
Simulation and Modeling.
Statistics
Big Data/Analytics.
Computer Applications.
Program transformation (Computer programming)
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