Biometry: The Principles and Practice of Statistics in Biological Research

  title={Biometry: The Principles and Practice of Statistics in Biological Research},
  author={Robert R. Sokal and F. James Rohlf},
1. Introduction 2. Data in Biology 3. Computers and Data Analysis 4. Descriptive Statistics 5. Introduction to Probability Distributions 6. The Normal Probability Distribution 7. Hypothesis Testing and Interval Estimation 8. Introduction to Analysis of Variance 9. Single-Classification Analysis of Variance 10. Nested Analysis of Variance 11. Two-Way and Multiway Analysis of Variance 12. Statistical Power and Sample Size in the Analysis of Variance 13. Assumptions of Analysis of Variance 14… Expand
Bivariate linear models in neurobiology: problems of concept and methodology
The underlying assumptions and statistics of the method most frequently used: ordinary linear regression, principal axis and standard major axis are focused on. Expand
Use of statistical techniques in analysis of biological data
In this study, a few techniques/tests have been described for checking the normality of a given set of data and the assumptions underlying the ANOVA have been discussed. Expand
Determining sexual dimorphism in frog measurement data: integration of statistical significance, measurement error, effect size and biological significance.
It is demonstrated that frog measurement data meet assumptions for clearly defined statistical hypothesis testing with statistical linear models rather than those of exploratory multivariate techniques such as principal components, correlation or correspondence analysis. Expand
Assessment of morphometric variation in natural populations: the inadequacy of the univariate approach
It is shown that even conselvative interpretations of the univariate results can lead to erroneous systematic conclusions, and that MANOVA is the correct statistical test for evaluating overall group differences. Expand
Further difficulties with multifactorial analysis of variance: random and nested factors and independence of data.
  • D. Morrison
  • Biology, Medicine
  • Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
  • 2002
An analysis of variance from the recent literature is discussed to illustrate the potential pitfalls when these characteristics are treated inappropriately, in the hope that such problems can be avoided in the future. Expand
Methodological tools
1. In this chapter we discuss the best methodological tools for visually and statistically comparing predictions of the metabolic theory of ecology to data. 2. Visualizing empirical data to determineExpand
On the misuse of residuals in ecology : testing regression residuals vs . the analysis of covariance
1. An analysis of variance (  ) or other linear models of the residuals of a simple linear regression is being increasingly used in ecology to compare two or more groups. Such a procedureExpand
On the misuse of residuals in ecology: testing regression residuals vs. the analysis of covariance
The residual index is an ad hoc sequential procedure with no statistical justification, unlike the well-known ancova, and it is suggested that a t-test or an anova of the residuals should never be used in place of an anCova to study condition or any other variable. Expand
Statistical Properties of Ratios. I. Empirical Results
Atchley, W. R., C. T. Gaskins, and D. Anderson (Departments of Biological Sciences, Animal Sciences, and Biomedical Engineering and Computer Medicine, Texas Tech University, Lubbock, Texas 79409)Expand
Unexpected failures of recommended tests in basic statistical analyses of ecological data
Abstract. Ecologists, when analyzing the output of simple experiments, often have to compare statistical samples that simultaneously are of uneven size, unequal variance and distribute non-normally.Expand