Mathematical statistics - Data processing.
Overview
Works: | 62 works in 43 publications in 43 languages |
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Titles
Computer age statistical inference : = algorithms, evidence, and data science /
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Using MATLAB to solve statistical problems = a practical guide to the book "Statistics for chemical and process engineers" /
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Core concepts in data analysis = summarization, correlation and visualization /
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R through Excel = a spreadsheet interface for statistics, data analysis, and graphics /
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Statistical analysis and data display = an intermediate course with examples in R /
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Towards advanced data analysis by combining soft computing and statistics
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Excel 2007 for educational and psychological statistics = a guide to solving practical problems /
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The R software = fundamentals of programming and statistical analysis /
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Computing statistics under interval and fuzzy uncertainty = applications to computer science and engineering /
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Two-way analysis of variance = statistical tests and graphics using R /
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Problem solving and data analysis using Minitab = a clear and easy guide to six sigma methodology /
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An introduction to statistical computing = a simulation-based approach /
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Advances in complex data modeling and computational methods in statistics
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An introduction to statistics with Python = with applications in the life sciences /
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Comparative approaches to using R and Python for statistical data analysis
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Statistical disclosure control for microdata = methods and applications in R /
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Data analysis with R : = a comprehensive guide to manipulating, analyzing, and visualizing data in R /
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Statistical data analysis using SAS = intermediate statistical methods /
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Attraction in numerical minimization = iteration mappings, attractors, and basins of attraction /
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Data science with MATLAB : = organizing data, descriptive statistics and visualization /
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Statistics and data analysis with MATLAB : = cluster analysis and applications /
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Core data analysis = summarization, correlation, and visualization /
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Computer age statistical inference = algorithms, evidence, and data science /
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Machine learning in production : = developing and optimizing data science workflows and applications /
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