語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
到查詢結果
[ author_sort:"wilcox, rand r." ]
切換:
標籤
|
MARC模式
|
ISBD
A guide to robust statistical methods
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A guide to robust statistical methodsby Rand R. Wilcox.
作者:
Wilcox, Rand R.
出版者:
Cham :Springer Nature Switzerland :2023.
面頁冊數:
xvii, 326 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Mathematical statistics.
電子資源:
https://doi.org/10.1007/978-3-031-41713-9
ISBN:
9783031417139$q(electronic bk.)
A guide to robust statistical methods
Wilcox, Rand R.
A guide to robust statistical methods
[electronic resource] /by Rand R. Wilcox. - Cham :Springer Nature Switzerland :2023. - xvii, 326 p. :ill., digital ;24 cm.
1. Introduction -- 2. The one-sample case -- 3. Comparing two independent groups -- 4. Comparing two dependent groups -- 5. Comparing multiple independent groups -- 6. Comparing multiple dependent groups -- 7. Robust regression estimators -- 8. Inferential methods based on robust regression estimators -- 9. Measures of association -- 10. Comparing groups when there is a covariate.
Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true-but they continue to perform well in situations where classic methods perform poorly. This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data. The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
ISBN: 9783031417139$q(electronic bk.)
Standard No.: 10.1007/978-3-031-41713-9doiSubjects--Topical Terms:
181877
Mathematical statistics.
LC Class. No.: QA276 / .W55 2023
Dewey Class. No.: 519.5
A guide to robust statistical methods
LDR
:02350nmm a2200325 a 4500
001
652256
003
DE-He213
005
20231025133459.0
006
m d
007
cr nn 008maaau
008
240327s2023 sz s 0 eng d
020
$a
9783031417139$q(electronic bk.)
020
$a
9783031417122$q(paper)
024
7
$a
10.1007/978-3-031-41713-9
$2
doi
035
$a
978-3-031-41713-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA276
$b
.W55 2023
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
.W667 2023
100
1
$a
Wilcox, Rand R.
$3
230082
245
1 2
$a
A guide to robust statistical methods
$h
[electronic resource] /
$c
by Rand R. Wilcox.
260
$a
Cham :
$b
Springer Nature Switzerland :
$b
Imprint: Springer,
$c
2023.
300
$a
xvii, 326 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
1. Introduction -- 2. The one-sample case -- 3. Comparing two independent groups -- 4. Comparing two dependent groups -- 5. Comparing multiple independent groups -- 6. Comparing multiple dependent groups -- 7. Robust regression estimators -- 8. Inferential methods based on robust regression estimators -- 9. Measures of association -- 10. Comparing groups when there is a covariate.
520
$a
Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true-but they continue to perform well in situations where classic methods perform poorly. This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data. The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
650
0
$a
Mathematical statistics.
$3
181877
650
1 4
$a
Statistical Theory and Methods.
$3
274054
650
2 4
$a
Applied Statistics.
$3
805583
650
2 4
$a
Methodology of Data Collection and Processing.
$3
921586
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer Nature eBook
856
4 0
$u
https://doi.org/10.1007/978-3-031-41713-9
950
$a
Mathematics and Statistics (SpringerNature-11649)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000234946
電子館藏
1圖書
電子書
EB QA276 .W667 2023 2023
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
https://doi.org/10.1007/978-3-031-41713-9
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入