Statistics explained : an introductory guide for life sciences / Steve McKillup.
Statistics Explained is a reader-friendly introduction to experimental design and statistics for undergraduate students in the life sciences, particularly those without a strong mathematical background. Topics are explained clearly and succinctly with minimum use of formulae and terminology, making...
Cambridge, UK ; New York :
Cambridge University Press,
- 'Doing science'
- hypotheses, experiments, and disproof
- Collecting and displaying data
- Introductory concepts of experimental design
- Probability helps you make a decision about your results
- Working from samples
- data, populations, and statistics
- Normal distributions
- tests for comparing the means of one and two samples
- Type 1 and type 2 errors, power, and sample size
- Single factor analysis of variance
- Multiple comparisons after ANOVA
- Two factor analysis of variance
- Important assumptions of analysis of variance: transformations and a test for equality of variances
- Two factor analysis of variance without replication, and nestedmil analysis of variance
- Relationships between variables: linear correlation and linear regression
- Simple linear regression
- Non-parametric statistics
- Non-parametric tests for nominal scale data
- Non-parametric tests for ratio, interval, or ordinal scale data
- Choosing a test
- Doing science responsibly and ethically.