Probability, Statistics and Life Cycle Assessment

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Bol This textbook discusses the use of uncertainty analysis and sensitivity analysis in environmental life cycle assessment (LCA). It gives a very broad overview of the field: probability theory, descriptive statistics, inferential statistics, error analysis, sensitivity analysis, decision theory, etc., all in relation to LCA. This textbook discusses the use of uncertainty analysis and sensitivity analysis in environmental life cycle assessment (LCA). This is a topic which has received a lot of attention by journals, including the leading (Springer) International Journal of Life Cycle Assessment. Despite its importance, no coherent textbook exists that summarizes the progress that has been made in the last 20 years. This book attempts to fill that gap. Its audience is practitioners (professional and academic) of LCA, teachers, and Ph.D. students. It gives a very broad overview of the field: probability theory, descriptive statistics, inferential statistics, error analysis, sensitivity analysis, decision theory, etc., all in relation to LCA. Much effort has been taken to give a balanced overview, with a uniform terminology and mathematical notation.

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This textbook discusses the use of uncertainty analysis and sensitivity analysis in environmental life cycle assessment (LCA). It gives a very broad overview of the field: probability theory, descriptive statistics, inferential statistics, error analysis, sensitivity analysis, decision theory, etc., all in relation to LCA. This textbook discusses the use of uncertainty analysis and sensitivity analysis in environmental life cycle assessment (LCA). This is a topic which has received a lot of attention by journals, including the leading (Springer) International Journal of Life Cycle Assessment. Despite its importance, no coherent textbook exists that summarizes the progress that has been made in the last 20 years. This book attempts to fill that gap. Its audience is practitioners (professional and academic) of LCA, teachers, and Ph.D. students. It gives a very broad overview of the field: probability theory, descriptive statistics, inferential statistics, error analysis, sensitivity analysis, decision theory, etc., all in relation to LCA. Much effort has been taken to give a balanced overview, with a uniform terminology and mathematical notation.


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