LEADER 03724nam 2200697I 450 001 9910460107103321 005 20200520144314.0 010 $a0-429-16914-0 035 $a(CKB)3710000000373045 035 $a(EBL)1446338 035 $a(SSID)ssj0001401016 035 $a(PQKBManifestationID)12572281 035 $a(PQKBTitleCode)TC0001401016 035 $a(PQKBWorkID)11344488 035 $a(PQKB)11480343 035 $a(MiAaPQ)EBC1446338 035 $a(CaSebORM)9781439885017 035 $a(Au-PeEL)EBL1446338 035 $a(CaPaEBR)ebr11165989 035 $a(OCoLC)908077475 035 $a(OCoLC)900220402 035 $a(EXLCZ)993710000000373045 100 $a20180611d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aData analysis and statistics for geography, environmental science, and engineering /$fby Miguel F. Acevedo 205 $a1st edition 210 1$aBoca Raton, FL :$cCRC Press, an imprint of Taylor and Francis,$d2012. 215 $a1 online resource (549 p.) 300 $aDescription based upon print version of record. 311 $a1-4398-8501-X 311 $a1-4665-9221-4 320 $aIncludes bibliographical references. 327 $aFront Cover; Contents; Preface; Acknowledgments; Author; Chapter 1 - Introduction; Chapter 2 - Probability Theory; Chapter 3 - Random Variables, Distributions, Moments, and Statistics; Chapter 4 - Exploratory Analysis and Introduction to Inferential Statistics; Chapter 5 - More on Inferential Statistics: Goodness of Fit, Contingency Analysis, and Analysis of Variance; Chapter 6 - Regression; Chapter 7 - Stochastic or Random Processes and Time Series; Chapter 8 - Spatial Point Patterns; Chapter 9 - Matrices and Linear Algebra; Chapter 10 - Multivariate Models 327 $aChapter 11 - Dependent Stochastic Processes and Time SeriesChapter 12 - Geostatistics: Kriging; Chapter 13 - Spatial Auto-Correlation and Auto-Regression; Chapter 14 - Multivariate Analysis I: Reducing Dimensionality; Chapter 15 - Multivariate Analysis II: Identifying and Developing Relationships among Observations and Variables; Bibliography; Back Cover 330 3 $aProviding a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustainability, the book brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applicable across a variety of science and engineering disciplines. 606 $aGeography$xData processing 606 $aGeography$xStatistical methods 606 $aEnvironmental sciences$xData processing 606 $aEnvironmental sciences$xStatistical methods 606 $aEngineering$xData processing 606 $aEngineering$xStatistical methods 608 $aElectronic books. 615 0$aGeography$xData processing. 615 0$aGeography$xStatistical methods. 615 0$aEnvironmental sciences$xData processing. 615 0$aEnvironmental sciences$xStatistical methods. 615 0$aEngineering$xData processing. 615 0$aEngineering$xStatistical methods. 676 $a519.5 700 $aAcevedo$b Miguel F.$0930402 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910460107103321 996 $aData analysis and statistics for geography, environmental science, and engineering$92092817 997 $aUNINA