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Experimental design for the life sciences / Graeme D. Ruxton, Nick Colegrave.

By: Contributor(s): Material type: TextTextPublication details: Oxford : Oxford University Press, c2006.Edition: 2nd edDescription: xviii, 162 p. : ill. ; 25 cmISBN:
  • 9780199285112 (pbk.) :
  • 9780199285112
Subject(s): DDC classification:
  • 570.724 RUX
LOC classification:
  • QH323.5
Incomplete contents:
1.Why you need to care about design -- 1.1 Why experiments need to be designed -- 1.2 The cost of poor design -- 1.3 The relationship between experimental design and statistics -- 1.4Why good experimental design is particularly important to life scientists -- 2.Starting with a well-defined hypothesis -- 2.1 Why your experiment should be focused: questions, hypotheses and predictions -- 2.2 Producing the strongest eveidence with which to challenge a hypothesis -- 2.3Staisfying sceptics: the Devil\'s advocate -- 2.4 The importance of a pilot study and preliminary data -- 2.5 Experimental manipulatioin versus natural variation -- 2.6 Deciding whether to work in the field or the laboratory -- 2.7In vivo versus in vitro studies -- 2.8 There is no perfect study -- 3.Between-individual variation, replication and sampling -- 3.1Between-individual variation -- 3.2 Replication -- 3.3 Pseudoreplication -- 3.4Randomization -- 3.5 Selecting the appropriate number of replicates -- 4.Different experimental designs -- 4.1 Controls -- 4.2 Completely randomized and factorial experiments -- 4.3 Blocking -- 4.4 Within-subject designs -- 4.5 Split-plot designs (sometimes called-unit designs) -- 5.Taking measurements -- 5.1Calibration -- 5.2 Inaccuracy and imprecision -- 5.3 Intra-observer variability -- 5.4 Inter-observer variability -- 5.5 Defining categories -- 5.6 Observer effects -- 5.7 Recording data 5.8 Computers and automated data collection -- 5.9 Floor and ceiling effects -- 5.10 Observer bias -- 5.11 Taking measurements of humans and animals in the laboratory -- 6.Final thoughts -- 6.1 How to select the levels for a treatment -- 6.2 Subsampling: more wood or more trees? -- 6.3 Using unbalanced groups for ethical reasons -- 6.4 Other sampling schemes -- 6.5 Latin square designs -- 6.6 More on interactions -- 6.7 Dealing with human subjects.
Summary: Providing students with clear and practical advice on how best to organise experiments and collect data so as to make the subsequent analysis easier and their conclusions more robust, this text assumes no specialist knowledge.
Holdings
Item type Current library Call number Copy number Status Date due Barcode
Long Loan TUS: Midlands, Main Library Athlone General Lending 570.724 RUX (Browse shelf(Opens below)) 1 Available 201445
Long Loan TUS: Midlands, Main Library Athlone General Lending 570.724 RUX (Browse shelf(Opens below)) 1 Available 201446

Previous ed.: 2003.

Includes bibliographical references and index.

1.Why you need to care about design -- 1.1 Why experiments need to be designed -- 1.2 The cost of poor design -- 1.3 The relationship between experimental design and statistics -- 1.4Why good experimental design is particularly important to life scientists -- 2.Starting with a well-defined hypothesis -- 2.1 Why your experiment should be focused: questions, hypotheses and predictions -- 2.2 Producing the strongest eveidence with which to challenge a hypothesis -- 2.3Staisfying sceptics: the Devil\'s advocate -- 2.4 The importance of a pilot study and preliminary data -- 2.5 Experimental manipulatioin versus natural variation -- 2.6 Deciding whether to work in the field or the laboratory -- 2.7In vivo versus in vitro studies -- 2.8 There is no perfect study -- 3.Between-individual variation, replication and sampling -- 3.1Between-individual variation -- 3.2 Replication -- 3.3 Pseudoreplication -- 3.4Randomization -- 3.5 Selecting the appropriate number of replicates -- 4.Different experimental designs -- 4.1 Controls -- 4.2 Completely randomized and factorial experiments -- 4.3 Blocking -- 4.4 Within-subject designs -- 4.5 Split-plot designs (sometimes called-unit designs) -- 5.Taking measurements -- 5.1Calibration -- 5.2 Inaccuracy and imprecision -- 5.3 Intra-observer variability -- 5.4 Inter-observer variability -- 5.5 Defining categories -- 5.6 Observer effects -- 5.7 Recording data 5.8 Computers and automated data collection -- 5.9 Floor and ceiling effects -- 5.10 Observer bias -- 5.11 Taking measurements of humans and animals in the laboratory -- 6.Final thoughts -- 6.1 How to select the levels for a treatment -- 6.2 Subsampling: more wood or more trees? -- 6.3 Using unbalanced groups for ethical reasons -- 6.4 Other sampling schemes -- 6.5 Latin square designs -- 6.6 More on interactions -- 6.7 Dealing with human subjects.

Providing students with clear and practical advice on how best to organise experiments and collect data so as to make the subsequent analysis easier and their conclusions more robust, this text assumes no specialist knowledge.

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