|
|
|
|
Leader |
LDR
|
|
cam i 00 |
Control # |
1
|
|
2019944285 |
Control # Id |
3
|
|
DLC |
Date |
5
|
|
20220111141415.0 |
Fixed Data |
8
|
|
190621r20192019nyua b 001 0 eng d |
LC Card |
10
|
|
$a 2019944285 |
ISBN |
20
|
|
$a9781541618510$q(hardcover) |
ISBN |
20
|
|
$a1541618513$q(hardcover) |
Local Ctrl # |
35
|
|
$a(OCoLC)on1112668483 |
Obsolete |
39
|
|
$a327765$cTLC |
Cat. Source |
40
|
|
$aNjBwBT$beng$cPNX$erda$dOCLCO$dOCLCQ$dCLE$dYDX$dUAP$dOCLCF$dLHL$dRCJ$dDLC |
Authen. Ctr. |
42
|
|
$alccopycat |
LC Call |
50
|
00 |
$aQA276.12$b.S665 2019 |
Dewey Class |
82
|
04 |
$a519.5$223 |
ME:Pers Name |
100
|
1 |
$aSpiegelhalter, D. J.$eauthor. |
Title |
245
|
14 |
$aThe art of statistics :$bhow to learn from data /$cDavid Spiegelhalter. |
Edition |
250
|
|
$aFirst US edition. |
Tag 264 |
264
|
1 |
$aNew York :$bBasic Books,$c2019. |
Phys Descrpt |
300
|
|
$axvi, 426 pages :$billustrations ;$c25 cm |
Tag 336 |
336
|
|
$atext$btxt$2rdacontent |
Tag 337 |
337
|
|
$aunmediated$bn$2rdamedia |
Tag 338 |
338
|
|
$avolume$bnc$2rdacarrier |
Note:Bibliog |
504
|
|
$aIncludes bibliographical references and index. |
Note:Content |
505
|
00 |
$gIntroduction --$tGetting things done in proportion : categorical data and percentages --$tSummarizing and communicating numbers, lots of numbers --$tWhy are we looking at data anyway? : populations and measurement --$tWhat causes what? --$tModelling relationships using regression --$tAlgorithms, analytics and prediction --$tHow sure can we be about what is going on? : estimates and intervals --$tProbability : the language of uncertainty and variability --$tPutting probability and statistics together --$tAnswering questions and claiming discoveries --$tLearning from experience the Bayesian way --$tHow things go wrong --$tHow we can do statistics better --$gIn conclusion. |
Abstract |
520
|
|
$aShows how to apply statistical reasoning to real-world problems. This isn't simply memorizing formulas or using the tools in a spreadsheet: he emphasizes the importance of clarifying questions, assumptions, and expectations, and- more importantly- knowing how to responsibly interpret the results the software generates. |
Subj:Topical |
650
|
0 |
$aStatistics$vPopular works. |