Muutke küpsiste eelistusi

Introductory Probability and Statistics: Applications for Forestry and Natural Sciences [Kõva köide]

(University of British Columbia, Canada), (University of Alabama, USA), (University of British Columbia, Canada), (University of British Columbia, Canada)
  • Formaat: Hardback, 448 pages, kõrgus x laius: 244x172 mm
  • Ilmumisaeg: 12-Jun-2008
  • Kirjastus: CABI Publishing
  • ISBN-10: 1845932757
  • ISBN-13: 9781845932756
Teised raamatud teemal:
  • Kõva köide
  • Hind: 108,10 €*
  • * saadame teile pakkumise kasutatud raamatule, mille hind võib erineda kodulehel olevast hinnast
  • See raamat on trükist otsas, kuid me saadame teile pakkumise kasutatud raamatule.
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Lisa soovinimekirja
Introductory Probability and Statistics: Applications for Forestry and Natural SciencesSuurem pilt
  • Formaat: Hardback, 448 pages, kõrgus x laius: 244x172 mm
  • Ilmumisaeg: 12-Jun-2008
  • Kirjastus: CABI Publishing
  • ISBN-10: 1845932757
  • ISBN-13: 9781845932756
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781845932756.html
Märksõnad:
With interest growing in areas of forestry, conservation and other natural sciences, the need to organize and tabulate large amounts of forestry and natural science information has become a necessary skill.
Previous attempts of applying statistical methods to these areas tend to be over-specialized and of limited use; an elementary text using methods, examples and exercise that are relevant to forestry and the natural sciences is long overdue. This book utilities basic descriptive statistics and probability, as well as commonly used statistical inferential tools to introduce topics that are common place in a forestry context such as hypothesis texting, design of experiments, sampling methods, nonparametric tests and statistical quality control. It also contains examples and exercise drawn from the fields of forestry, wood science, and conservation.
List of Figures
ix
List of Tables
xiii
Preface xv
Statistics and Data: What do Numbers have to do with Trees?
1(8)
What is Statistics?
1(1)
Data
2(1)
Measurement Scales
3(1)
Data Collection
4(5)
Exercises
6(3)
Descriptive Statistics: Making Sense of Data
9(26)
Tables
9(5)
Graphical Tools
14(5)
Measures of Central Location
19(4)
Measures of Variation
23(6)
Measures of Position
29(1)
Computers and Statistical Software
30(5)
Exercises
31(4)
Probability: the Foundation of Statistics
35(26)
Sample Space and Events
35(4)
Counting Techniques
39(5)
Probability
44(2)
Rules for Probabilities
46(7)
Bayes' Theorem
53(8)
Exercises
55(6)
Random Variables and Probability Distributions: Outcomes of Random Experiments
61(18)
Random Variables
61(1)
Probability Distributions
62(4)
Mean of a Random Variable
66(4)
Variance of a Random Variable
70(2)
Rules of Mathematical Expectations Related to the Mean and Variance
72(7)
Exercises
75(4)
Some Discrete Probability Distributions: Describing Data that are Counted
79(14)
Uniform Distribution
79(1)
Binomial and Multinomial Distributions
80(4)
Hypergeometric and Multivariate Hypergeometric Distributions
84(3)
Geometric and Negative Binomial Distributions
87(1)
Poisson Distribution
88(5)
Exercises
89(4)
Continuous Distributions and the Normal Distribution: Describing Data that are Measured
93(18)
Uniform Distribution
93(2)
Exponential Distribution
95(1)
Normal Distribution
96(8)
Normal Approximation to the Binomial Distribution
104(7)
Exercises
107(4)
Sampling Distributions: The Foundation of Inference
111(36)
Sampling and Sampling Distributions
111(4)
Sampling Distribution of the Mean
115(7)
Sampling Distribution of the Sample Proportion
122(3)
Sampling Distribution of the Differences between Two Means
125(1)
Independent populations
125(7)
Dependent populations
132(2)
Sampling Distribution of the Differences between Two Proportions
134(2)
Sampling Distribution of the Variance
136(2)
Sampling Distribution of the Ratios of Two Variances
138(2)
Some Concluding Remarks about Sampling Distributions
140(7)
Exercises
141(6)
Estimation: Determining the Value of Population Parameters
147(26)
Point Estimation
147(1)
Interval Estimation
148(1)
Estimating the Mean
149(6)
Estimating Proportions
155(2)
Estimating the Difference between Two Means
157(5)
Independent samples
157(4)
Dependent samples
161(1)
Estimating the Difference of Two Proportions
162(1)
Estimating the Variance
163(2)
Estimating the Ratio of Two Variances
165(8)
Exercises
167(6)
Tests of Hypotheses: Making Claims about Population Parameters
173(28)
Statistical Hypothesis and Test Procedures
173(6)
Tests Concerning Means
179(3)
Tests Concerning Proportions
182(1)
Tests Concerning Variances
183(2)
Tests Concerning the Difference between Two Means
185(5)
Independent populations
185(4)
Dependent populations
189(1)
Tests Concerning the Difference between Two Proportions
190(2)
Tests Concerning the Ratio of Two Variances
192(4)
p-Values
196(5)
Exercises
196(5)
Goodness-of-fit and Test for Independence: Testing Distributions
201(16)
Goodness-of-fit Test
201(5)
Test for Independence
206(11)
Exercises
213(4)
Regression and Correlation: Relationships between Variables
217(34)
Simple Linear Regression
218(21)
Determination of the regression equation
218(6)
Regression analysis
224(6)
Sampling distributions and tests concerning the regression coefficients and predictions
230(6)
Lack of fit
236(3)
Correlation Analysis
239(1)
Multiple Regression
240(4)
Non-linear Models
244(7)
Exercises
246(5)
Analysis of Variance: Testing Differences between Several Means
251(26)
One-way Analysis of Variance
252(9)
Multiple Comparisons
261(4)
Bonferroni's Procedure
262(1)
Scheffe's Method
263(2)
Test for Equality of Variances
265(1)
Two-way Analysis of Variance
266(11)
Exercises
274(3)
Sampling Methods and Design of Experiments: Collecting Data
277(10)
Sampling Methods
277(3)
Simple random sampling
278(1)
Stratified random sampling
278(1)
Two-stage sampling
278(1)
Systematic sampling
279(1)
Survey design
280(1)
Experimental Designs
280(7)
Completely randomized design
281(1)
Randomized complete block design
282(1)
Latin square design
283(2)
Factorial experiments
285(2)
Non-parametric Tests: Testing when Distributions are Unknown
287(18)
Sign Test
288(3)
Wilcoxon Signed Rank Test
291(2)
Wilcoxon Rank Sum Test
293(3)
Kruskal---Wallis Test
296(1)
Runs Test
297(3)
Spearman's Rank Correlation Test
300(5)
Exercises
301(4)
Quality Control: Statistics for Production and Processing
305(12)
Variable Charts
308(4)
Attribute Charts
312(5)
Exercises
313(4)
Bibliography
317(4)
Solutions to Odd-numbered Questions
321(28)
Appendix A
349(36)
Binomial Probabilities
351(7)
Poisson Probabilities
358(5)
Areas Under the Normal Curve
363(1)
Random Numbers
364(1)
Critical Values for the t Distribution
365(1)
Critical Values for the X2 Distribution
366(1)
Critical Values for the F Distribution
367(6)
Critical Values for the r Distribution
373(4)
Critical Values for the Bonferroni t Statistic
377(1)
Critical Values for the Wilcoxon Signed Rank Test
378(1)
Critical Values for the Wilcoxon Rank Sum Test
379(2)
Critical Values for the Runs Test
381(2)
Critical Values for Spearman's Rank Correlation Coefficient Test
383(2)
Appendix B
385(2)
Summation Notation
385(2)
Glossary 387(14)
Index 401