Download Free Population Parameters Book in PDF and EPUB Free Download. You can read online Population Parameters and write the review.

Ecologists and environmental managers rely on mathematical models, both to understand ecological systems and to predict future system behavior. In turn, models rely on appropriate estimates of their parameters. This book brings together a diverse and scattered literature, to provide clear guidance on how to estimate parameters for models of animal populations. It is not a recipe book of statistical procedures. Instead, it concentrates on how to select the best approach to parameter estimation for a particular problem, and how to ensure that the quality estimated is the appropriate one for the specific purpose of the modelling exercise. Commencing with a toolbox of useful generic approaches to parameter estimation, the book deals with methods for estimating parameters for single populations. These parameters include population size, birth and death rates, and the population growth rate. For such parameters, rigorous statistical theory has been developed, and software is readily available. The problem is to select the optimal sampling design and method of analysis. The second part of the book deals with parameters that describe spatial dynamics, and ecological interactions such as competition, predation and parasitism. Here the principle problems are designing appropriate experiments and ensuring that the quantities measured by the experiments are relevant to the ecological models in which they will be used. This book will be essential reading for ecological researchers, postgraduate students and environmental managers who need to address an ecological problem through a population model. It is accessible to anyone with an understanding of basic statistical methods and population ecology. Unique in concentrating on parameter estimation within modelling. Fills a glaring gap in the literature. Not too technical, so suitable for the statistically inept. Methods explained in algebra, but also in worked examples using commonly available computer packages (SAS, GLIM, and some more specialised packages where relvant). Some spreadsheet based examples also included.
Information regarding population status and abundance of rare species plays a key role in resource management decisions. Ideally, data should be collected using statistically sound sampling methods, but by their very nature, rare or elusive species pose a difficult sampling challenge. Sampling Rare or Elusive Species describes the latest sampling designs and survey methods for reliably estimating occupancy, abundance, and other population parameters of rare, elusive, or otherwise hard-to-detect plants and animals. It offers a mixture of theory and application, with actual examples from terrestrial, aquatic, and marine habitats around the world. Sampling Rare or Elusive Species is the first volume devoted entirely to this topic and provides natural resource professionals with a suite of innovative approaches to gathering population status and trend data. It represents an invaluable reference for natural resource professionals around the world, including fish and wildlife biologists, ecologists, biometricians, natural resource managers, and all others whose work or research involves rare or elusive species.
Need to know how to build and test models based on data? Intermediate Statistics For Dummies gives you the knowledge to estimate, investigate, correlate, and congregate certain variables based on the information at hand. The techniques you’ll learn in this book are the same techniques used by professionals in medical and scientific fields. Picking up right where Statistics For Dummies left off, this straightforward, easy-to-follow book guides you beyond Central Limit Theorem and hypothesis tests and immerses you in flavors of regression, ANOVA, and nonparametric procedures. Unlike regular statistics books, this guide provides full explanations of intermediate statistical ideas; computer input dissection; an extensive number of examples, tips, strategies, and warnings; and clear, concise step-by-step procedures—all in a language you can understand. You’ll soon discover how to: Analyze data and base models off of your data Make predictions using regression Compare many means with ANOVA Test models using Chi-square Dealing with abnormal data In addition, this book includes a list of wrong statistical conclusions and common questions that professors ask using computer output. This book also adopts a nonlinear approach, making it possible to skip to the information you need without having to read previous chapters. With Intermediate Statistics For Dummies, you’ll have all the tools you need to make important decisions in all types of professional areas—from biology and engineering to business and politics!
This Eighth Edition of Social Statistics for a Diverse Society continues to emphasize intuition and common sense, while demonstrating that social science is a constant interplay between methods of inquiry and important social issues. Recognizing that today’s students live in a world of growing diversity and richness of social differences, authors Chava Frankfort-Nachmias and Anna Leon-Guerrero use research examples that show how statistics is a tool for understanding the ways in which race, class, gender, and other categories of experience shape our social world and influence social behavior. In addition, guides for reading and interpreting the research literature help students acquire statistical literacy, while SPSS demonstrations and a rich variety of exercises help them hone their problem-solving skills.
EBOOK: USING STATISTICS IN ECONOMICS
The 5th Edition of this popular introduction to statistics for the medical and health sciences has undergone a significant revision, with several new chapters added and examples refreshed throughout the book. Yet it retains its central philosophy to explain medical statistics with as little technical detail as possible, making it accessible to a wide audience. Helpful multi-choice exercises are included at the end of each chapter, with answers provided at the end of the book. Each analysis technique is carefully explained and the mathematics kept to minimum. Written in a style suitable for statisticians and clinicians alike, this edition features many real and original examples, taken from the authors' combined many years' experience of designing and analysing clinical trials and teaching statistics. Students of the health sciences, such as medicine, nursing, dentistry, physiotherapy, occupational therapy, and radiography should find the book useful, with examples relevant to their disciplines. The aim of training courses in medical statistics pertinent to these areas is not to turn the students into medical statisticians but rather to help them interpret the published scientific literature and appreciate how to design studies and analyse data arising from their own projects. However, the reader who is about to design their own study and collect, analyse and report on their own data will benefit from a clearly written book on the subject which provides practical guidance to such issues. The practical guidance provided by this book will be of use to professionals working in and/or managing clinical trials, in academic, public health, government and industry settings, particularly medical statisticians, clinicians, trial co-ordinators. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations.
Statistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching experience. With a wealth of hands-on exercises and online resources created by the author, practice your skills using the data sets and R scripts from the book with detailed screencasts that accompany each script. This book is ideal for anyone looking to: • Complete an introductory course in statistics • Prepare for more advanced statistical courses • Gain the transferable analytical skills needed to interpret research from across the social sciences • Learn the technical skills needed to present data visually • Acquire a basic competence in the use of R and RStudio. This edition also includes a gentle introduction to Bayesian methods integrated throughout. The author has created a wide range of online resources, including: over 90 R scripts, 36 datasets, 37 screen casts, complete solutions for all exercises, and 130 multiple-choice questions to test your knowledge.
When it comes to learning statistics, Mann delivers the information that business professionals need. The new edition incorporates the most up-to-date methods and applications to present the latest information in the field. It focuses on explaining how to apply the concepts through case studies and numerous examples. Data integrated throughout the chapters come from a wide range of disciplines and media sources. Over 200 examples are included along with marginal notes and step-by-step solutions. The Decide for Yourself feature also helps business professionals explore real-world problems and solutions.
Applications of Hypothesis Testing for Environmental Science presents the theory and application of hypothesis testing in environmental science, allowing researchers to carry out suitable tests for decision-making on a variety of issues. This book works as a step-by-step resource to provide understanding of the concepts and applications of hypothesis testing in the field of environmental science. The tests are presented in simplified form without relying on complex mathematical proofs to allow researchers to easily locate the most appropriate test and apply it to real-world situations. Each example is accompanied by a case study showing the application of the method to realistic data. This book provides step-by-step guidance in analyzing and testing various environmental data for researchers, postgraduates and graduates of environmental sciences, as well as academics looking for a book that includes case studies of the applications of hypothesis testing. It will also be a valuable resource for researchers in other related fields and those who are not familiar with the use of statistics who may need to analyze data or perform hypothesis tests in their research. Includes step-by-step tutorials to aid in the understanding of procedures and allowing implementation of suitable tests Presents the theory of hypothesis testing in a simple yet thorough manner without complex mathematical proofs Describes how to implement hypothesis testing in analyzing and interpretation environmental science data
Today econometrics has been widely applied in the empirical study of economics. As an empirical science, econometrics uses rigorous mathematical and statistical methods for economic problems. Understanding the methodologies of both econometrics and statistics is a crucial departure for econometrics. The primary focus of this book is to provide an understanding of statistical properties behind econometric methods. Following the introduction in Chapter 1, Chapter 2 provides the methodological review of both econometrics and statistics in different periods since the 1930s. Chapters 3 and 4 explain the underlying theoretical methodologies for estimated equations in the simple regression and multiple regression models and discuss the debates about p-values in particular. This part of the book offers the reader a richer understanding of the methods of statistics behind the methodology of econometrics. Chapters 5–9 of the book are focused on the discussion of regression models using time series data, traditional causal econometric models, and the latest statistical techniques. By concentrating on dynamic structural linear models like state-space models and the Bayesian approach, the book alludes to the fact that this methodological study is not only a science but also an art. This work serves as a handy reference book for anyone interested in econometrics, particularly in relevance to students and academic and business researchers in all quantitative analysis fields.