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Experimental Design and Data Analysis for Biologists
Abstract
An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and links to software.
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“VIFs did not reveal collinearity problems, as indicated by the largest value being <4 (51) (event model 2.59; anticipation model 2.43; defection model 1.98; intergroup conflict type model 2.74; persistence model 2.03; reduced event model 2.72).”
From Oxytocin reactivity during intergroup conflict in wild chimpanzees (2017) · cites this paper as [51]
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Sorted by citations
Items 1,001–1,025 of 1,025
Vogel, E. R., & Janson, C. H. (2006) · American Journal of Primatology · doi:10.1002/ajp.20368 · Cited by 86
“We used the Akaike information criterion (AIC) to reduce the regression model to a smaller number of explanatory variables [Quinn & Keough, 2002].”
Primate brain architecture and selection in relation to sex
Lindenfors, P., Nunn, C. L., & Barton, R. A. (2007) · BMC Biology · doi:10.1186/1741-7007-5-20 · Cited by 86
Placentation and Maternal Investment in Mammals
Capellini, I., Venditti, C., & Barton, R. A. (2011) · The American Naturalist · doi:10.1086/657435 · Cited by 81
“We coded placentation with dummy variables (Quinn and Keough 2002).”
InfluentialFakhar, K., Hastings, E., Butson, C. R., Foote, K. D., Zeilman, P., & Okun, M. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0058665 · Cited by 80
Allopatric speciation within a cryptic species complex of Australasian octopuses
Amor, M. D., Norman, M. D., Cameron, H. E., & Strugnell, J. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0098982 · Cited by 79
Humans or LLMs as the Judge? A Study on Judgement Bias
Chen, G. H., Chen, S., Liu, Z., Jiang, F., & Wang, B. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2024.emnlp-main.474 · Cited by 76
Eye for an eyespot: how iridescent plumage ocelli influence peacock mating success
Dakin, R., & Montgomerie, R. (2013) · Behavioral Ecology · doi:10.1093/beheco/art045 · Cited by 75
Biochar vs. clay: Comparison of their effects on nutrient retention of a tropical Arenosol
Beusch, C., Cierjacks, A., Böhm, J., Mertens, J., Bischoff, W.-A., de Araújo Filho, J. C., & Kaupenjohann, M. (2019) · Geoderma · doi:10.1016/j.geoderma.2018.09.043 · Cited by 65
Bedard, M.-J., Joyal, C. C., Godbout, L., & Chantal, S. (2009) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/acp052 · Cited by 62
“If these procedures were not successful, regressions were conducted on rank-transformed data (Quinn and Keough, 2002).”
MethodReciprocity and trades in wild West African chimpanzees
Gomes, C. M., & Boesch, C. (2011) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-011-1227-x · Cited by 59
“Statistical analysis General results are presented using the trimmed mean, which is insensitive to outliers (Quinn and Keough 2002), the first quartile (Q1), and third quartile (Q3) throughout.”
MethodInfluentialCenci, U., Sibbald, S. J., Curtis, B. A., Kamikawa, R., Eme, L., Moog, D., Henrissat, B., Maréchal, E., Chabi, M., Djemiel, C., et al. (2018) · BMC Biology · doi:10.1186/s12915-018-0593-5 · Cited by 53
Szöcs, E., & Schäfer, R. B. (2015) · Environmental Science and Pollution Research · doi:10.1007/s11356-015-4579-3 · Cited by 52
Cattaneo, E., Laczko, E., Buffoli, F., Zorzi, F., Bianco, M. A., Menigatti, M., Bartosova, Z., Haider, R., Helmchen, B., Sabates‐Bellver, J., et al. (2011) · EMBO Molecular Medicine · doi:10.1002/emmm.201100141 · Cited by 44
“RMA-preprocessed expression data were subjected to unsupervised analysis PCA and supervised multivariate analyses (BGA-based on CoA, and RDA; Supporting Information; Baty et al, 2008; Culhane et al, 2002; Quinn and Kenough, 2006; Ringner, 2008).”
MethodMixture-based clustering for the ordered stereotype model
Fernández, D., Arnold, R., & Pledger, S. (2016) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2014.11.004 · Cited by 39
Simple pond restoration measures increase dragonfly (Insecta: Odonata) diversity
Janssen, A., Hunger, H., Konold, W., Pufal, G., & Staab, M. (2018) · Biodiversity and Conservation · doi:10.1007/s10531-018-1539-5 · Cited by 38
“Stable ordination solutions were centred and rotated until the first NMDS-axis explained maximum variance (Quinn and Keough 2002).”
BackgroundOliveira, J. A., West, C. P., Afif, E., & Palencia, P. (2017) · Agronomy Journal · doi:10.2134/agronj2016.07.0440 · Cited by 35
Season-long expression of Cry1Ac and Cry2Ab proteins in Bollgard II cotton in Australia
Knight, K., Head, G., & Rogers, J. (2013) · Crop Protection · doi:10.1016/j.cropro.2012.10.014 · Cited by 32
Husbandry and enclosure influences on penguin behavior and conservation breeding
Marshall, A. R., Deere, N. J., Little, H. A., Snipp, R., Goulder, J., & Mayer-Clarke, S. (2016) · Zoo Biology · doi:10.1002/zoo.21313 · Cited by 33
A family of experiments on test-driven development
Santos, A., Vegas, S., Dieste, O., Uyaguari, F., Tosun, A., Fucci, D., Turhan, B., Scanniello, G., Romano, S., Karac, I., et al. (2021) · Empirical Software Engineering · doi:10.1007/s10664-020-09895-8 · Cited by 30
“, points with abnormally high X values—in our case, reported experience levels) that pull the regression lines towards each other, especially if sample size is small [41].”
BackgroundAllomaternal care, brains and fertility in mammals: who cares matters
Heldstab, S. A., Isler, K., Burkart, J. M., & van Schaik, C. P. (2019) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-019-2684-x · Cited by 29
Shephard, J. M., Catterall, C. P., & Hughes, J. M. (2004) · Emu - Austral Ornithology · doi:10.1071/mu03043 · Cited by 27
Using a bird community index to evaluate national parks in the urbanized national capital region
Goodwin, S. E., & Shriver, W. G. (2014) · Urban Ecosystems · doi:10.1007/s11252-014-0363-2 · Cited by 13
Pathak, A. K., Sharma, M., Katiyar, S. K., Katiyar, S., & Nagar, P. K. (2020) · Scientific Reports · doi:10.1038/s41598-020-79023-5 · Cited by 9
Shahedi, F., Ahmadi, J., Sharifi, T., Seyedhasani, S. N., Abdollahi, M., Shaabani, N., & Sarmadi, M. (2020) · Journal of Education and Health Promotion · doi:10.4103/jehp.jehp_753_19 · Cited by 5
“The sample size was selected based on minimum sample size in experimental studies.[18] Inclusion criteria included pass in Hematology I course and have a same teacher.”
MethodSeban, P., Urban, K., & Sikl, R. (2025) · Instructional Science · doi:10.1007/s11251-024-09686-4 · Cited by 5
Metadata
- Authors
- Quinn, G. P., & Keough, M. J.
- Affiliations
- Monash University (AU)
- The University of Melbourne (AU)
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2002-03-21
- OpenAlex
- W1489838709
- Cited by
- 10,674
- References
- 0
- Citations by year
- 2026: 200 · 2025: 218 · 2024: 239 · 2023: 250 · 2022: 275 · 2021: 394 · 2020: 448 · 2019: 430 · 2018: 446 · 2017: 473 · 2016: 528 · 2015: 625 · 2014: 763 · 2013: 719 · 2012: 675
- FWCI
- 50.52
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Cambridge University Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- experimental design, statistical analysis, biology, hypothesis testing, Bayesian analysis, linear models, generalized linear models, logistic regression, analysis of variance, repeated measures, log-linear models, multivariate analysis, classification, ordination, exploratory data analysis, assumption checking
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