國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Introduction to R for terrestrial ec...

Lakicevic, Milena.

Introduction to R for terrestrial ecologybasics of numerical analysis, mapping, statistical tests and advanced application of R /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to R for terrestrial ecologyby Milena Lakicevic, Nicholas Povak, Keith M. Reynolds.
其他題名:	basics of numerical analysis, mapping, statistical tests and advanced application of R /
作者:	Lakicevic, Milena.
其他作者:	Povak, Nicholas.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xvii, 158 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	R (Computer program language)
電子資源:	https://doi.org/10.1007/978-3-030-27603-4
ISBN:	9783030276034$q(electronic bk.)

Introduction to R for terrestrial ecologybasics of numerical analysis, mapping, statistical tests and advanced application of R /
Lakicevic, Milena.

Introduction to R for terrestrial ecologybasics of numerical analysis, mapping, statistical tests and advanced application of R /[electronic resource] :by Milena Lakicevic, Nicholas Povak, Keith M. Reynolds. - Cham :Springer International Publishing :2020. - xvii, 158 p. :ill. (some col.), digital ;24 cm.

1. Types of Data in R -- 2. Numerical Analysis -- 3. Creating Maps -- 4. Basic Statistical Tests -- 5. Predictive Modeling with Machine Learning Applications -- Appendix.

This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced applications of the R programming language. The main objective of the textbook is to serve as a guide for undergraduate students, who have no previous experience with R, but part of the textbook is dedicated to advanced R applications, and will also be useful for Masters and PhD students, and professionals. The textbook deals with solving specific programming tasks in R, and tasks are organized in terms of gradually increasing R proficiency, with examples getting more challenging as the chapters progress. The main competencies students will acquire from this textbook are: manipulating and processing data tables performing statistical tests creating maps in R This textbook will be useful in undergraduate and graduate courses in Advanced Landscape Ecology, Analysis of Ecological and Environmental Data, Ecological Modeling, Analytical Methods for Ecologists, Statistical Inference for Applied Research, Elements of Statistical Methods, Computational Ecology, Landscape Metrics and Spatial Statistics.

ISBN: 9783030276034$q(electronic bk.)

Standard No.: 10.1007/978-3-030-27603-4doiSubjects--Topical Terms:

210846
R (Computer program language)

LC Class. No.: QA276.45.R3 / L35 2020

Dewey Class. No.: 519.50285536

Introduction to R for terrestrial ecologybasics of numerical analysis, mapping, statistical tests and advanced application of R /
LDR:02436nmm a2200337 a 4500 001 573416
003 DE-He213
005 20200120161044.0
006 m d
007 cr nn 008maaau
008 200928s2020 sz s 0 eng d
020 $a 9783030276034$q(electronic bk.)
020 $a 9783030276027$q(paper)
024 7 $a 10.1007/978-3-030-27603-4 $2 doi
035 $a 978-3-030-27603-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.45.R3 $b L35 2020
072 7 $a UMX $2 bicssc
072 7 $a COM051010 $2 bisacsh
072 7 $a UMX $2 thema
072 7 $a UMC $2 thema
082 0 4 $a 519.50285536 $2 23
090 $a QA276.45.R3 $b L192 2020
100 1 $a Lakicevic, Milena. $3 860723
245 1 0 $a Introduction to R for terrestrial ecology $h [electronic resource] : $b basics of numerical analysis, mapping, statistical tests and advanced application of R / $c by Milena Lakicevic, Nicholas Povak, Keith M. Reynolds.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xvii, 158 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 1. Types of Data in R -- 2. Numerical Analysis -- 3. Creating Maps -- 4. Basic Statistical Tests -- 5. Predictive Modeling with Machine Learning Applications -- Appendix.
520 $a This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced applications of the R programming language. The main objective of the textbook is to serve as a guide for undergraduate students, who have no previous experience with R, but part of the textbook is dedicated to advanced R applications, and will also be useful for Masters and PhD students, and professionals. The textbook deals with solving specific programming tasks in R, and tasks are organized in terms of gradually increasing R proficiency, with examples getting more challenging as the chapters progress. The main competencies students will acquire from this textbook are: manipulating and processing data tables performing statistical tests creating maps in R This textbook will be useful in undergraduate and graduate courses in Advanced Landscape Ecology, Analysis of Ecological and Environmental Data, Ecological Modeling, Analytical Methods for Ecologists, Statistical Inference for Applied Research, Elements of Statistical Methods, Computational Ecology, Landscape Metrics and Spatial Statistics.
650 0 $a R (Computer program language) $3 210846
650 0 $a Ecology $x Mathematical models. $3 188710
650 0 $a Ecology $x Data processing. $3 575771
650 1 4 $a Programming Languages, Compilers, Interpreters. $3 274102
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 274067
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 348605
650 2 4 $a Terrestial Ecology. $3 273944
650 2 4 $a Theoretical Ecology/Statistics. $3 276089
700 1 $a Povak, Nicholas. $3 860724
700 1 $a Reynolds, Keith M. $3 293294
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-3-030-27603-4
950 $a Computer Science (Springer-11645)