國立虎尾科技大學 |

Statistical Design and Analysis of Biological Experiments

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Statistical Design and Analysis of Biological Experiments/ by Hans-Michael Kaltenbach.
作者:	Kaltenbach, Hans-Michael.
面頁冊數:	XIV, 269 p. 70 illus., 7 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Statistical Theory and Methods. -
電子資源:	https://doi.org/10.1007/978-3-030-69641-2
ISBN:	9783030696412

Statistical Design and Analysis of Biological Experiments
Kaltenbach, Hans-Michael.

Statistical Design and Analysis of Biological Experiments[electronic resource] /by Hans-Michael Kaltenbach. - 1st ed. 2021. - XIV, 269 p. 70 illus., 7 illus. in color.online resource. - Statistics for Biology and Health,2197-5671. - Statistics for Biology and Health,.

Principles of Experimental Design -- Review of Statistical Concepts -- Planning for Precision and Power -- Comparing More than Two Groups -- Comparing Treatment Groups with Linear Contrasts -- Multiple Treatment Factors: Factorial Designs -- Improving Precision and Power: Blocked Designs -- Split-Unit Designs -- Many Treatment Factors: Fractional Factorial Designs -- Experimental Optimization with Response Surface Methods -- References -- Index.

This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.

ISBN: 9783030696412

Standard No.: 10.1007/978-3-030-69641-2doiSubjects--Topical Terms:

671396
Statistical Theory and Methods.

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Statistical Design and Analysis of Biological Experiments
LDR:03745nam a22004095i 4500 001 1051330
003 DE-He213
005 20210815003903.0
007 cr nn 008mamaa
008 220103s2021 sz | s |||| 0|eng d
020 $a 9783030696412 $9 978-3-030-69641-2
024 7 $a 10.1007/978-3-030-69641-2 $2 doi
035 $a 978-3-030-69641-2
050 4 $a QA276-280
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
100 1 $a Kaltenbach, Hans-Michael. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 887895
245 1 0 $a Statistical Design and Analysis of Biological Experiments $h [electronic resource] / $c by Hans-Michael Kaltenbach.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a XIV, 269 p. 70 illus., 7 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Statistics for Biology and Health, $x 2197-5671
505 0 $a Principles of Experimental Design -- Review of Statistical Concepts -- Planning for Precision and Power -- Comparing More than Two Groups -- Comparing Treatment Groups with Linear Contrasts -- Multiple Treatment Factors: Factorial Designs -- Improving Precision and Power: Blocked Designs -- Split-Unit Designs -- Many Treatment Factors: Fractional Factorial Designs -- Experimental Optimization with Response Surface Methods -- References -- Index.
520 $a This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.
650 1 4 $a Statistical Theory and Methods. $3 671396
650 0 $a Bioinformatics. $3 583857
650 0 $a Statistics . $3 1253516
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030696405
776 0 8 $i Printed edition: $z 9783030696429
776 0 8 $i Printed edition: $z 9783030696436
830 0 $a Statistics for Biology and Health, $x 1431-8776 $3 1254965
856 4 0 $u https://doi.org/10.1007/978-3-030-69641-2
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)