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Statistical Methods for Environmental and Agricultural Sciences
โ Scribed by Reza Hoshmand (Author)
- Publisher
- CRC Press
- Year
- 1998
- Leaves
- 458
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
The first edition of this book, popular around the world, is surpassed only by this new Second Edition. Improvements such as new and revised exercises, a broad range of practical and relevant case studies, and expanded theoretical concepts make this even better for users of statistics. The book emphasizes the practical application of statistics and provides examples in various fields of environmental and agriculture sciences. Because it uses simple, non-mathematical language to present statistical techniques, the reader requires only a familiarity with elementary algebra and mathematical notations to understand and apply the concepts described.
This logically organized book covers the following topics: Part 1 introduces statistical concepts as they apply to different fields of environmental and agriculture sciences and provides descriptive measures of central tendency and variability; Part 2 covers probability and sampling concepts used in inferential statistics; Part 3 presents parametric methods in hypothesis testing, which include research designs; Part 4 discusses a number of nonparametric techniques; Part 5 explains tests of association and prediction; and lastly, analysis of change over time is detailed in Part 6. The appendices contain statistical tables for reference purposes.
โฆ Table of Contents
Mathematical Symbols and Notations
General Mathematical Symbols
PART I. DESCRIPTIVE STATISTICS IN ENVIRONMENTAL AND AGRICULTURE SCIENCES
1. The What and Why of Statistics for Environmental and Agricultural Sciences
What Is Statistics?
Why Study Statistics for Environmental and Agriculture Sciences
2. Descriptive Statistical Measures
Frequency Distribution
Measures of Central Tendency
Measures of Variability
PART II. INFERENTIAL STATISTICS IN ENVIRONMENTAL AND AGRICULTURE SCIENCES
3. Probability Theory
Measurement of Probability
Optional Topic: Principles of Counting
Bayes` Theorem
Probability Distributions
4. An Introduction to Sampling Concepts
Key Sampling Concepts
Sampling Techniques in Environmental and Agriculture Sciences
Sampling Distributions
5. Estimation of Parameters: Means and Percentages
Point Estimation
Interval Estimation
Estimating Population Mean: s Known
Estimating Population Mean: s Unknown
Use of Student t Distribution
Interval Estimation of the Population Percentage
Determining Sample Size
PART III. TESTS OF COMPARISON: PARAMETRIC METHODS
6. Hypothesis Testing: One-Sample
Steps in Hypothesis Testing
Test of a Mean : Large Sample
Test of a Mean: Small Sample
Test of a Proportion
An Alternative Approach to Hypothesis Testing
Relationship between a and b Risk
7. Hypothesis Testing: Two-Sample
Introduction: Questions about Differences
Two-Sample Test of Means: Large Sample
Two-Sample Test of Means: Small Sample
Two-Sample Test of Percentage: Large Sample
8. Analysis of Variance
One-Factor Analysis of Variance
Two-Factor Analysis of Variance
Latin Square Design
PART IV. NONPARAMETRIC METHODS
9. Chi-Square Analysis
Test of Differences Among Proportions
Chi-Square Test of Independence
Test of Goodness-of-Fit
Tests of Homogeneity
10. Additional Nonparametric Methods
Sign Test
Wilcoxon Signed-Rank Test
Mann-Whitney U Test
Spearman Rank Correlation Coefficient
PART V. TEST OF ASSOCIATION AND PREDICTION
11. Simple Linear Regression and Correlation
Introduction: Bivariate Relationships
Regression Analysis
Standard Error of Estimate
Correlation Analysis
An Application Using Computer Packages
Optional Topic: Curvilinear Regression Analysis
12. Multiple Regression
Estimating Multiple Regression Equation: Least Squares Method
Standard Error of Estimate
Multiple Correlation Analysis
Interference Concerning the Regression and Correlation Coefficients
Assumptions and Problems in Multiple Linear Regression
Optional Topic: Curvilinear Multiple Regression Analysis
A Computer Application
PART VI. ANALYSIS OF CHANGE OVER TIME
13. Time Series Analysis
Secular Trend Analysis
Seasonal Variation
Identifying Cycles and Irregular Variation
14. Index Numbers
Basic Construction Techniques
Pitfalls and Some Considerations in Use of Index Numbers
APPENDICES
Binomial Distribution
Areas Under the Standard Normal Probability Distribution Between the Mean and Successive Values of z
Normal Deviates for Statistical Estimation and Hypothesis Testing
Random Digits
Critical Values of t
F Distribution
Chi-Square (c2) Distribution
Wilcoxon T Values
Critical Values of U in the Mann-Whitney Test
Values of dL and dU for the Durbin Watson Test
Index
Chapters contain Introductions, Learning Objectives, Chapter Summaries, Case Studies, and Review Questions.
Supplementary materials include a solution manual to all chapter problems, master transparencies for all figures and tables in the text, and powerpoint lecture outlines.
โฆ Subjects
Environment & Agriculture;Agriculture & Environmental Sciences;Agriculture;Bioscience;Biology;Statistics for the Biological Sciences;Earth Sciences;Earth Sciences;Geochemistry;Geostatistics
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