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Statistical And Data Handling Skills in Biology
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Does the lead in petrol fumes affect the growth of roadside plants?
The ability to expertly analyse statistical data is a crucial skill in the biological sciences it is fundamental to fully understanding what your experiments are actually telling you and so being able to answer your research questions.
Statistical and Data Handling Skills in Biology gives you everything you need to understand and use statistical tests within your studies and future independent research.
Written in a straight-forward and easy to understand style it presents all of the tests you will need throughout your studies, and shows you how to select the right tests to get the most out of your experiments. All of this is done in the context of biological examples so you can see just how relevant a skill this is, and how becoming fully proficient will make you a more rounded scientist.
This 4th edition has been thoroughly updated throughout and now includes detailed coverage of the free statistical package R studio and a new chapter on how to write about and present statistics in papers, theses and reports. The first chapter has also been revised to introduce students to the need for and ideas behind statistical analysis.
Clear explanation with step by step detail of how to carry out a wide range of statistical analyses will help you to quickly gain understanding and confidence in this essential area.
Useful decision charts will help you to select the right statistical test and gain confidence in answering your research questions.
Real world examples in each chapter will help you to develop an applied understanding of the full range of statistical techniques
Self-assessment problems scenarios at the end of each chapter enable you to practice applying your understanding of a technique, thereby improving your confidence in using numbers. Guided answers allow you to check your understanding.
Statistical and Data Handling Skills in Biology 4th edition is idealfor any biomedic or environmental scientist getting to grips with statistical analysis for use in class on as part of independent study.
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Fler böcker av Roland Ennos
1 An introduction to statistics
1.1 Becoming a biologist
1.2 Awkward questions
1.3 Why biologists have to repeat everything
1.4 Why biologists have to bother with statistics
1.5 Why statistical logic is so strange
1.6 Why there are so many statistical tests
1.7 Using the decision chart
1.8 Using this text
2 Dealing with variability
2.2 Examining the distribution of data
2.3 The normal distribution
2.4 Describing the normal distribution
2.5 The variability of samples
2.6 Confidence limits
2.7 Presenting descriptive statistics and confidence limits
2.8 Introducing computer programs
2.9 Calculating descriptive statistics
2.10 Self-assessment problems
3 Testing for normality and transforming data
3.1 The importance of normality testing
3.2 The ShapiroWilk test
3.3 What to do if your data has a significantly different distribution from the normal
3.4 Examining data in practice
3.5 Transforming data
3.6 The complete testing procedure
3.7 Self-assessment problems
4 Testing for differences from an expected value or between two groups
4.2 Why we need statistical tests for differences
4.3 How we test for differences
4.4 One- and two-tailed tests
4.5 The types of t test and their non-parametric equivalents
4.6 The one-sample t test
4.7 The paired t test
4.8 The two-sample t test
4.9 Introduction to non-parametric tests for differences
4.10 The one-sample sign test
4.11 The Wilcoxon matched pairs test
4.12 The MannWhitney U test
4.13 Self-assessment problems
5 Testing for differences between more than two groups: ANOVA and its non-parametric equivalents
5.2 One-way ANOVA
5.3 Deciding which groups are different post hoc tests
5.4 Presenting the results of one-way ANOVAs
5.5 Repeated measures ANOVA
5.6 The KruskalWallis test
5.7 The Friedman test
5.8 Two-way ANOVA
5.9 The ScheirerRayHare Test
5.10 Nested ANOVA
5.11 Self-assessment problems
6 Investigating relationships
6.2 Examining data for relationships
6.3 Examining graphs
6.4 Linear relationships
6.5 Statistical tests for linear relationships
6.8 Studying common non-linear relationships
6.9 Dealing with non-normally distributed data: rank correlation
6.10 Self-assessment problems
7 Dealing with categorical data
7.2 The problem of variation
7.3 The x2 test for differences
7.4 The x2 test for association
7.5 Validity x2 of tests
7.6 Logistic regre...