A Primer Of Ecological Statistics

A Primer Of Ecological Statistics by Nicholas J. Gotelli. Download in PDF, EPUB, and Mobi Format for read it on your Kindle device, PC, phones or tablets. A Primer Of Ecological Statistics books. Click Download for free ebooks.

A Primer Of Ecological Statistics

A Primer Of Ecological Statistics
Author: Nicholas J. Gotelli
Publisher: Sinauer Associates, Incorporated
ISBN: 9780878932696
Size: 39.82 MB
Format: PDF, Mobi
View: 4798
Get Books

Part I: FundamentaIs of Probability and Statistical Thinking. Chapter 1: An lntroduction to Probability. What Is Probability? Measuring Probability. The Probability of a Single Event. Prey Capture by Carnivorous Plants. Estimating Probabilities by Sampling . Problems in the Definition Probability The Mathematics of Probability. Defining the Sample Space. Complex and Shared Events: Combining Simple Probabilities. Probability Calcu1ations: Milkweeds and Caterpillars. Complex and Shared Events: Rules for Combining Sets, Conditional Probabilities. Bayes' Theorem. Chapter 2: Random Variables and Probability Distributions. Discrete Random Variables. Bernoulli Random Variables. An Example of a Bernoulli Trial. Many Bernoulli Trials = A Binomial Randorn Variable. The Binomial Distribution. Poisson Random Variables. An Example of a Poisson Random Variable: Distribution of aRare Plant. The Expected Value of a Discrete Random Variable. The Variance of a Discrete Random Variable. Continuous Random Variables. Uniform Random Variables. The Expected Value of a Continuous Random Variable. Normal Random Variables. Useful Properties of the Normal Distribution. Other Continuous Random Variables. The Central Limit Theorem. Chapter 3: Summary Statistics: Measuresof Location and Spread. Measures of Location. The Arithmetic Mean Other Means. Other Measures of Location: The Median and the Mode. When to Use Each Measure of Location. Measures of Spread. The Variance and the Standard Deviation. The Standard Error of the Mean. Skewness, Kurtosis, and Central Moments. Quantiles. Using Measures of Spread. Some Philosophical Issues Surrounding Summary Statistics. Confidence Intervals. Generalized Confidence lntervals. Chapter 4: Framing and Testing Hypotheses. Scientific Methods. Deduction and lnduction. Moderrn-Day lnduction: Bayesian lnference. The Hypothetico-Deductive Method. Testing Statistical Hypotheses. Statistical Hypotheses versus Scientific Hypotheses. Statistical Significance and P - Values. Errors in Hypothesis Testing. Parameter Estimation and Prediction. Chapter 5:Three Frameworks for Statistical Analysis. Sample Problem. Monte Carlo Analysis. Step 1: Specifying the Test Statistic. Step 2: Creating the Null Distribution. Step 3: Deciding on a One- or Two- Tailed Test. Step 4: Calculating the Tail Probability. Assumptions of the Monte Carlo Method. Advantages and Disadvantages of the Monte Carlo Method. Parametric Analysis. Step 1: Specifyjng the Test Statistic. Step 2: Specifying the Null Distribution. Step 3: Calculating the Tail Probability. Assumptions of the Parametric Method. Advantages and Disadvantages of the Parametric Method. Least-Squares Parameter Estimates 246 Variance Components and the Coefficient of Determination. Hypothesis Tests with Regression. The Anatomy of an ANOVA Table. Other Tests and Confidence IntervaIs. Assumptions of Regression. Diagnostic Tests For Regression. Plotting ResiduaIs. Other Diagnostic Plots. The lnfluence Function. Monte Cado and Bayesian Analyses. Linear Regression Using Monte Cado Methods. Linear Regression Using Bayesian Methods. Other Kinds of Regression Analyses. Robust Regression. Quantile Regression. Logistic Regression. Non-Linear Regression. Multiple Regression. Path AnaIysis. Model Selection Cri teria. Model Selection Methods for Multiple Regression. Model Selection Methods in Path Analysis. Bayesian Model Selection. Chapter 10: The Analysis Of VarianceSymbols and Labels in ANOVA. ANOVA and Partitioning of the Sum of Squares. The Assumptions of ANOVA. Hypothesis Tests with ANOVA. Constructing F- Ratios. A Bestiary of ANOVA Tables. Randomized Block. Nested ANOVA. Two- Way ANOVA. ANOVA for Three- Way and n- Way Designs. Split-Plot ANOVA. Repeated Measures ANOVA. ANCOVA. Random versus Fixed Factors in ANOVA. Partitioning the Variance in ANOVA. After ANOVA: Plotting and Understanding Interaction Terms. Plotting Results from One-Way ANOVAs. Plotting Results from Two- Way ANOVAs. Understanding the lnteraction Term. Plotting Results fram ANCOVAs. Comparing Means. A Posteriori Comparisons. A Priori Contrasts. Bonferroni Corrections and the Problem of Multiple Tests. Chapter 11: The Analysis of Categorical Data. Two- Way Contingency Tables. Organizing the Data. Are the Variables lndependent? Testing the Hypothesis: Pearson's Chi-square Test. An Alternative to Pearson's Chi-Square: The G- Test. The Chi-square Test and the G- Test for R x C Tables. Which Test To Choose? Multi- Way Contingency Tables. Organizing the Data. On to Multi- Way Tables! Bayesian Approaches to Contingency Tables. Tests for Goodness-of-Fit. Goodness-of- Fit Tests for Discrete Distributions. Testing Goodness-of-Fit for Continuous. Distributions: The Kolmogorov-Smirnov Test. Chapter 12: The Analysis Of Multivariate Data. Approaching Multivariate Data. The Need for Matrix Algebra. Comparing Multivariate Means. Comparing Multivariate Means of Two Samples: Hotelling's y2 Test. Comparing Multivariate Means of More Than Two Samples: A Simple MANOVA. The Multivariate Normal Distribution. Testing for Multivariate Normality. Measurements of Multivariate Distance. Measuring Distances between Two IndividuaIs. Measuring Distances Between Two Groups. Other Measurements of Distance. Ordination. Principal Component Analysis 406 Factor Analysis. Principal Coordinates Analysis. Correspondence Analysis. Non-Metric Multidimensional Scaling. Advantages and Disadvantages of Ordination.Classification . Cluster Analysis. Choosing a Clustering Method. Discriminant Analysis. Advantages and Disadvantages of Classification. Multivariate Multiple Regression. Redundancy Analysis.
A Primer of Ecological Statistics
Language: en
Pages: 510
Authors: Nicholas J. Gotelli, Aaron M. Ellison, Senior Ecologist and Senior Research Fellow Harvard Forest Aaron M Ellison
Categories: Science
Type: BOOK - Published: 2004 - Publisher: Sinauer Associates, Incorporated
Part I: FundamentaIs of Probability and Statistical Thinking. Chapter 1: An lntroduction to Probability. What Is Probability? Measuring Probability. The Probability of a Single Event. Prey Capture by Carnivorous Plants. Estimating Probabilities by Sampling . Problems in the Definition Probability The Mathematics of Probability. Defining the Sample Space. Complex and
A Primer of Ecological Statistics
Language: en
Pages: 614
Authors: Nicholas J. Gotelli, Aaron M. Ellison
Categories: Science
Type: BOOK - Published: 2013 - Publisher: Sinauer Associates Incorporated
This book takes a broad-based approach that emphasizes the historical, cultural, political, religious, social, and economic factors that underlie an understanding of both global and domestic terrorism. This unique text-reader combines original essays with the best of the existing literature on terrorism. Each chapter of this text begins with an
A Primer of Ecology
Language: en
Pages: 236
Authors: Nicholas J. Gotelli
Categories: Biologie des populations - Modèles mathématiques
Type: BOOK - Published: 1998 - Publisher:
A detailed exposition of the most common mathematical models in population and community ecology, covering exponential and logistic population growth, age-structured demography, metapopulation dynamics, competition, predation, and island biogeography. Intended to demystify ecological models and the math behind them by deriving the models from first principles. The primer may be
Exam Prep for: A Primer of Ecological Statistics
Language: en
Pages:
Authors: Nicholas J. Gotelli
Categories: Biologie des populations - Modèles mathématiques
Type: - Published: - Publisher:
Books about Exam Prep for: A Primer of Ecological Statistics
Statistical Ecology
Language: en
Pages: 337
Authors: John A. Ludwig, LUDWIG QUARTET, Reynolds J F, James F. Reynolds
Categories: Science
Type: BOOK - Published: 1988-05-18 - Publisher: John Wiley & Sons
Ecological community data. Spatial pattern analysis. Species-abundance relations. Species affinity. Community classification. Community ordination. Community interpretation.
A Primer of Ecology with R
Language: en
Pages: 388
Authors: M. Henry Stevens
Categories: Science
Type: BOOK - Published: 2009-06-02 - Publisher: Springer Science & Business Media
Provides simple explanations of the important concepts in population and community ecology. Provides R code throughout, to illustrate model development and analysis, as well as appendix introducing the R language. Interweaves ecological content and code so that either stands alone. Supplemental web site for additional code.
Ecological Statistics
Language: en
Pages: 400
Authors: Gordon A. Fox, Simoneta Negrete-Yankelevich, Vinicio J. Sosa
Categories: Science
Type: BOOK - Published: 2015-01-29 - Publisher: OUP Oxford
The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These
A Primer in Biological Data Analysis and Visualization Using R
Language: en
Pages: 160
Authors: Gregg Hartvigsen
Categories: Science
Type: BOOK - Published: 2014-02-18 - Publisher: Columbia University Press
R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the
Environmental and Ecological Statistics with R
Language: en
Pages: 440
Authors: Song S. Qian
Categories: Mathematics
Type: BOOK - Published: 2009-08-19 - Publisher: CRC Press
Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R connects applied statistics to the environmental and ecological fields. It follows the general approach to solving a statistical modeling problem, covering model specification, parameter estimation, and model evaluation. The author uses many examples to illustrate the statistical
Handbook of Environmental and Ecological Statistics
Language: en
Pages: 854
Authors: Alan E. Gelfand, Montserrat Fuentes, Jennifer A. Hoeting, Richard Lyttleton Smith
Categories: Mathematics
Type: BOOK - Published: 2019-01-15 - Publisher: CRC Press
This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its