The modern ecologist usually works in both the field and laboratory, uses statistics and computers, and often works with ecological concepts that are model-based, if not model-driven. How do we make the field and laboratory coherent? How do we link models and data? How do we use…
by Fisher, L.
fromProbability and mathematical statistics
The t-test; Two-sample t-test; The k-sample comparison of means(one-way analysis of variance); The balanced two-way factorial design without interaction; Estimation and more on factorial designs; The latin square; Confidence sets, simultaneous confidence intervals and multiple c…
"With the growing interest in areas of forestry, conservation and other natural sciences, the ability to organize and tabulate large amounts of information has become a necessary skill. Previous attempts of applying statistical methods to these areas have tended to be over-speci…
Nowadays, ecologists worldwide recognize the use of spatial analysis as essential. However, because of the fast-growing range of methods available, even an expert might occasionally find it challenging to choose the most appropriate one. Providing the ecological and statistical …
A systematic treatment of the statistical challenges that arise in environmental health studies and the use epidemiologic data in formulating public policy, at a level suitable for graduate students and epidemiologic researchers.
by Wilson, David B., Lipsey, Mark W.
fromApplied social research methods series
This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a…
"This book concerns adaptive tests of significance, which are statistical tests that use the data to modify the test procedures. The modification is used to reduce the influence of outliers. These adaptive tests are attractive because they are often more powerful than traditiona…
Basic mathematical redundancy models -- Formulation of optimal redundancy problems -- Method of Lagrange multipliers -- Steepest descent method -- Dynamic programming -- Universal generating functions -- Genetic algorithms -- Monte Carlo simulation -- Comments on calculation met…
The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate ap…
The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate ap…
