Experimental design and data analysis for biologists./ by Gerry P. Quinn, Victoria, Michael J. Keough,
Material type:
TextPublication details: United Kingdom ; Cambridge University , 2024.Edition: Second editionDescription: xix,387 p.; ill., 28cmISBN: - 9781107687677
- 570.151 QUE
| Cover image | Item type | Current library | Home library | Collection | Shelving location | Call number | Materials specified | Vol info | URL | Copy number | Status | Notes | Date due | Barcode | Item holds | Item hold queue priority | Course reserves | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Book | Central Library, University of Barishal | Department of Soil and Environmental Sciences | Shelve No 32 | 570.151 QUE 2024 (Browse shelf(Opens below)) | Available | 20127 |
Browsing Central Library, University of Barishal shelves,Shelving location: Shelve No 32,Collection: Department of Soil and Environmental Sciences Close shelf browser (Hides shelf browser)
| No cover image available | ||||||||
| 552 TYP The principles of petrology : an introduction to the science of rocks / | 552.1 TUI Igneous and metamorpic petrology / | 570 LOB Biology / | 570.151 QUE 2024 Experimental design and data analysis for biologists./ by | 570.15195 WES 2020 Statistical Methods in Biology : Design and Analysis of Experiments and Regression/by | 571.95 SHE Environmental Biology and Toxicology / | 571.95 SHE Environmental Biology and Toxicology / |
Revised edition of: Experimental design and data analysis for biologists / Gerry P. Quinn, Michael J. Keough. 2002.
Includes bibliographical references.
-- 1.1 Almost every biological theory or hypothesis is a model of how nature works.<br/> -- 1.2 We use data to separate wrong models from (possibly) correct ones (or bad models from less bad ones).<br/> -- 1.3 There are many ways to reach wrong conclusions!<br/> -- 1.4 There are also many ways to be right!<br/> -- 1.5 Our philosophy in this books.<br/> -- 1.6 How this book is structured.<br/> -- 1.7 A bit of housekeeping. 1. Introduction.<br/>
-- 2.1 Samples, population, and statistical inference.<br/> -- 2.2 Probability.<br/> -- 2.3 Probability distributions.<br/> -- 2.4 Frequentist ("classical") estimation.<br/> -- 2.5 Hypothesis testing.<br/> -- 2.6 Comments on frequentist inference.<br/> -- 2.7 Bayesian statistical inference. 2. Things to Know Before Proceeding.<br/>
-- 3.1 Sampling design.<br/> -- 3.2 Experimental design.<br/> -- 3.3 Sample size for detecting differences: power analysis.<br/> -- 3.4 Key points. 3. Sampling and Experimental Design.<br/>
There are no comments on this title.
Click on an image to view it in the image viewer