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

Statistical analysis of empirical da...

Pardo, Scott.

Statistical analysis of empirical datamethods for applied sciences /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical analysis of empirical databy Scott Pardo.
其他題名:	methods for applied sciences /
作者:	Pardo, Scott.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xi, 278 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Mathematical statistics.
電子資源:	https://doi.org/10.1007/978-3-030-43328-4
ISBN:	9783030433284$q(electronic bk.)

Statistical analysis of empirical datamethods for applied sciences /
Pardo, Scott.

Statistical analysis of empirical datamethods for applied sciences /[electronic resource] :by Scott Pardo. - Cham :Springer International Publishing :2020. - xi, 278 p. :ill., digital ;24 cm.

Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical methodology who seek guidance in defending their statistical decision-making in the worlds of research and practice. It is devoted to helping students and scholars find the information they need to select data analytic methods, and to speak knowledgeably about their statistical research processes. Each chapter opens with a conundrum relating to the selection of an analysis, or to explaining the nature of an analysis. Throughout the chapter, the analysis is described, along with some guidance in justifying the choices of that particular method. Designed to offer statistical knowledge to the non-specialist, this volume can be used in courses on research methods, or for courses on statistical applications to biological, medical, life, social, or physical sciences. It will also be useful to academic and industrial researchers in engineering and in the physical sciences who will benefit from a stronger understanding of how to analyze empirical data. The book is written for those with foundational education in calculus. However, a brief review of fundamental concepts of probability and statistics, together with a primer on some concepts in elementary calculus and matrix algebra, is included. R code and sample datasets are provided.

ISBN: 9783030433284$q(electronic bk.)

Standard No.: 10.1007/978-3-030-43328-4doiSubjects--Topical Terms:

181877
Mathematical statistics.

LC Class. No.: QA276 / .P373 2020

Dewey Class. No.: 519.5

Statistical analysis of empirical datamethods for applied sciences /
LDR:02485nmm a2200313 a 4500 001 572075
003 DE-He213
005 20200817172923.0
006 m d
007 cr nn 008maaau
008 200922s2020 sz s 0 eng d
020 $a 9783030433284$q(electronic bk.)
020 $a 9783030433277$q(paper)
024 7 $a 10.1007/978-3-030-43328-4 $2 doi
035 $a 978-3-030-43328-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276 $b .P373 2020
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
090 $a QA276 $b .P226 2020
100 1 $a Pardo, Scott. $3 736427
245 1 0 $a Statistical analysis of empirical data $h [electronic resource] : $b methods for applied sciences / $c by Scott Pardo.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xi, 278 p. : $b ill., digital ; $c 24 cm.
520 $a Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical methodology who seek guidance in defending their statistical decision-making in the worlds of research and practice. It is devoted to helping students and scholars find the information they need to select data analytic methods, and to speak knowledgeably about their statistical research processes. Each chapter opens with a conundrum relating to the selection of an analysis, or to explaining the nature of an analysis. Throughout the chapter, the analysis is described, along with some guidance in justifying the choices of that particular method. Designed to offer statistical knowledge to the non-specialist, this volume can be used in courses on research methods, or for courses on statistical applications to biological, medical, life, social, or physical sciences. It will also be useful to academic and industrial researchers in engineering and in the physical sciences who will benefit from a stronger understanding of how to analyze empirical data. The book is written for those with foundational education in calculus. However, a brief review of fundamental concepts of probability and statistics, together with a primer on some concepts in elementary calculus and matrix algebra, is included. R code and sample datasets are provided.
650 0 $a Mathematical statistics. $3 181877
650 1 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 348605
650 2 4 $a Bayesian Inference. $3 825978
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 274067
650 2 4 $a Statistics for Social Sciences, Humanities, Law. $3 825904
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-3-030-43328-4
950 $a Mathematics and Statistics (Springer-11649)