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Applied Statistics for Environmental Science with R Al-Karkhi Alqaraghuli
Product Description
Applied Statistics for Environmental Science with R
Covers the theory and application of statistical techniques used in environmental science
Abbas F. M. Al-Karkhi (Author), Wasin A. A. Alqaraghuli (Author)
9780128186220
Paperback / softback, published 13 September 2019
240 pages
27.6 x 21.6 x 1.6 cm, 0.66 kg
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.
1. Multivariate Data2.]
Applied Statistics for Environmental Science with R Al-Karkhi Alqaraghuli
Applied Statistics for Environmental Science with R
Covers the theory and application of statistical techniques used in environmental science
Abbas F. M. Al-Karkhi (Author), Wasin A. A. Alqaraghuli (Author)
9780128186220
Paperback / softback, published 13 September 2019
240 pages
27.6 x 21.6 x 1.6 cm, 0.66 kg
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.
1. Multivariate Data2.]
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