Introduction to probability and statistics for ecosystem managers: simulation and resampling
Explores computer-intensive probability and statistics for ecosystem management decision making Simulation is an accessible way to explain probability and stochastic model behavior to beginners. This book introduces probability and statistics to future and practicing ecosystem managers by providing a comprehensive treatment of these two areas. The author presents a self.
Read More ↓Title Statements
- Full title :Introduction to probability and statistics for ecosystem managers : simulation and resampling / Timothy C. Haas, Sheldon B. Lubar School of Business, University of Wisconsin-Milwaukee, USA.
Summary
Explores computer-intensive probability and statistics for ecosystem management decision making Simulation is an accessible way to explain probability and stochastic model behavior to beginners. This book introduces probability and statistics to future and practicing ecosystem managers by providing a comprehensive treatment of these two areas. The author presents a self.
Read More ↓Edition Statements
- Publication Date:2013.
Publication Statements
- Publisher(s):Wiley
- Place of Publication:Chichester, West Sussex, United Kingdom
- Language:eng
- Publication Date:2013.
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9781118636237, 1118636236, 9781118636220, 1118636228, 9781118636244, 1118636244, 1118636201, 9781118636206
- oclc:ocn841051232
- LC Classification:QH77.3.S73
- Dewey Decimal:333.72
Table of Contents
1. Introduction -- 1.1. The textbook's purpose -- 1.1.1. The textbook's focus on ecosystem management -- 1.1.2. Reader level, prerequisites, and typical reader jobs -- 1.2. The textbook's pedagogical approach -- 1.2.1. General points -- 1.2.2. Use of this textbook for self-study -- 1.2.3. Learning resources -- 1.3. Chapter summaries -- 1.4. Installing and running R Commander -- 1.4.1. Running R -- 1.4.2. Starting an R Commander session -- 1.4.3. Terminating an R Commander session -- 1.5. Introductory R Commander session -- 1.6. Teaching probability through simulation -- 1.6.1. The frequentist statistical inference paradigm -- 1.7. Summary -- 2. Probability and simulation -- 2.1. Introduction -- 2.2. Basic probability -- 2.2.1. Definitions -- 2.2.2. Independence -- 2.3. Random variables -- 2.3.1. Definitions -- 2.3.2. Simulating random variables -- 2.3.3.A random variable's expected value (mean) and variance -- 2.3.4. Details of the normal (Gaussian) distribution.
2.3.5. Distribution approximations -- 2.4. Joint distributions -- 2.4.1. Definition -- 2.4.2. Mixed variables -- 2.4.3. Marginal distribution -- 2.4.4. Conditional distributions -- 2.4.5. Independent random variables -- …
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