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ISBN: 0128243015 0323851878 9780323851879 9780128243015 Year: 2020 Publisher: Cambridge, Massachusetts : Elsevier,
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Environmental sciences. --- Environmental science --- Science
Book
ISBN: 9780128142639 0128142634 0128142626 9780128142622 Year: 2018 Publisher: London, United Kingdom : Academic Press, an imprint of Elsevier,
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Food industry and trade --- R (Computer program language) --- Statistical methods. --- E-books --- GNU-S (Computer program language) --- Domain-specific programming languages --- Food --- Food preparation industry --- Food processing --- Food processing industry --- Food technology --- Food trade --- Agricultural processing industries --- Processed foods --- Processing
Book
ISBN: 0128186232 9780128186220 0128186224 9780128186237 Year: 2020 Publisher: Amsterdam, Netherlands ; Kidlington, Oxford, England ; Cambridge, Massachusetts : Elsevier,
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Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems.
Digital
ISBN: 9780128142639 0128142634 Year: 2019 Publisher: London, United Kingdom Academic Press, an imprint of Elsevier
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Digital
ISBN: 0128186232 9780128186220 0128186224 9780128186237 Year: 2019 Publisher: San Diego Elsevier
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Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems.
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