Biometry: the principles and practice of statistics in biological research
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York
Freeman
2012
|
| Edition: | 4. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. 891 - 908. - Hier auch später erschienene, unveränderte Nachdrucke |
| Physical Description: | XIX, 937 S. zahlr. graph. Darst. |
| ISBN: | 0716786044 9780716786047 |
Staff View
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Record in the Search Index
| _version_ | 1804138736010657792 |
|---|---|
| adam_text | Contents
Preface
x¡¡¡
Notes
on the Fourth Edition
xvii
1
Introduction
1
1.1
Some Definitions
1
1.2
The Development of Biometry
3
1.3
The Statistical Frame of Mind
5
2
Data in Biology
2.1
Samples and Populations
9
2.2
Variables in Biology
11
2.3
Accuracy and Precision of Data
13
2.4
Derived Variables
16
2.5
Frequency Distributions
19
3
Computers and Data Analysis
33
3.1
Computers
33
3.2
Software
35
3.3
Efficiency and Economy in Data Processing
37
4
Descriptive Statistics
39
40
44
45
47
49
49
51
54
55
4.1
The Arithmetic Mean
4.2
Other Means
4.3
The Median
4.4
The Mode
4.5
Sample Statistics and Parameters
4.6
The Range
4.7
The Standard Deviation
4.8
Coding Data Before Computation
4.9
The Coefficient of Variation
VII
viii Contents
5
Introduction
to Probability Distributions:
Binomial and
Poisson
59
5.1
Probability, Random Sampling, and Hypothesis Testing
60
5.2
The Binomial Distribution
68
5.3
The
Poisson
Distribution
78
5.4
Other Discrete Probability Distributions
87
6
The Normal Probability Distribution
93
6.1
Frequency Distributions of Continuous Variables
93
6.2
Properties of the Normal Distribution
95
6.3
A Model for the Normal Distribution
100
6.4
Applications of the Normal Distribution
102
6.5
Fitting a Normal Distribution to Observed Data
104
6.6
Skewness and Kurtosis
106
6.7
Graphic Methods
108
6.8
Other Continuous Distributions
117
7
Hypothesis Testing and Interval Estimation
119
7.1
Introduction to Hypothesis Testing: Randomization Approaches
120
7.2
Distribution and Variance of Means
131
7.3
Distribution and Variance of Other Statistics
137
7.4
The t-Distribution
140
7.5
More on Hypothesis Testing: Normally Distributed Data
142
7.6
Power of a Test
146
7.7
Tests of Simple Hypotheses Using the Normal and (-Distributions
148
7.8
The Chi-Square Distribution
154
7.9
Testing the Hypothesis Ho:
σ2 = σ2,
156
7.10
Introduction to Interval Estimation (Confidence Limits)
157
7.11
Confidence Limits Using Sample Standard Deviations
162
7.12
Confidence Limits for Variances
167
7.13
The Jackknife and the Bootstrap
168
8
Introduction to Analysis of Variance
177
8.1
Variances of Samples and Their Means
178
8.2
The f-Distribution
182
8.3
The Hypothesis Ho:
σ2 = σ2
187
8.4
Heterogeneity Among Sample Means
190
8.5
Partitioning the Total Sum of Squares
and Degrees of Freedom
197
Contents
IX
8.6
Model I Anova
200
8.7
Model II Anova
203
9
Single-Classification Analysis of Variance
207
9.1
Computational Formulas
208
9.2
General Case: Unequal and Equal
η
208
9.3
Special Case: Two Groups
220
9.4
Comparisons Among Means in a Model I Anova: Essential
Background
228
9.5
Comparisons Among Means: Special Methods
246
10
Nested Analysis of Variance
277
10.1
Nested Anova: Design
277
10.2
Nested Anova: Computation
280
10.3
Nested Anovas with Unequal Sample Sizes
301
Π
Two-Way and Multiway Analysis of Variance
319
11.1
Two-Way Anova: Design
319
11.2
Two-Way Anova with Equal Replication: Computation
321
11.3
Two-Way Anova: Hypothesis Testing
331
11.4
Two-Way Anova Without Replication
340
11.5
Paired Comparisons
349
11.6
The Factorial Design
354
11.7
A Three-Way Factorial Design
355
11.8
Higher-Order Factorial Anovas
365
11.9
Other Designs
370
11.10
Anova by Computer
372
12
Statistical Power and Sample Size in the
Analysis of Variance
379
12.1
Effect Size
379
12.2
Noncentral
t-
and F-Distributions and Confidence Limits
for Effect Sizes
382
12.3
Power in an Anova
390
12.4
Sample Size in an Anova
391
12.5
Minimum Detectable Difference
395
12.6
Post Hoc Power Analysis
396
12.7
Optimal Allocation of Resources in a Nested Design
397
12.8
Randomized Blocks and Other Two-Wav and Multiwav
Desie
ns
406
X
Contents
13
Assumptions of Analysis of Variance
409
13.1
A Fundamental Assumption
410
13.2
Independence
410
13.3
Homogeneity of Variances
413
13.4
Normality
422
13.5
Transformations
426
13.6
The Logarithmic Transformation
427
13.7
The Square Root Transformation
433
13.8
The
Box
-Сох
Transformation
435
13.9
The Arcsine Transformation
438
13.10
Nonparametric Methods in Lieu of Single-Classification
Anova
440
13.11
Nonparametric Methods in Lieu of Two-Way Anova
460
14
Linear Regression
471
14.1
Introduction to Regression
472
14.2
Models in Regression
475
14.3
The Linear Regression Equation
477
14.4
Hypothesis Testing in Regression
485
14.5
More Than One Value of
У
for Each Value of X
495
14.6
The Uses of Regression
506
14.7
Estimating X From
Y
511
14.8
Comparing Two Regression Lines
513
14.9
Linear Comparisons in Anovas
515
14.10
Examining Residuals and Transformations in Regression
524
14.11
Nonparametric Tests for Regression
532
14.12
Model II Regression
535
14.13
Effect Size, Power, and Sample Size in Regression
544
15
Correlation
551
15.1
Correlation Versus Regression
551
15.2
The Product-Moment Correlation Coefficient
554
15.3
Computing the Product-Moment Correlation Coefficient
562
15.4
The Variance of Sums and Differences
565
15.5
Hypothesis Tests for Correlations
567
15.6
Applications of Correlation
577
15.7
Nonparametric Tests for Association
580
15.8
Major Axes and Confidence Regions
588
15.9
Effect Size, Power, and Sample Size
592
Contents
X¡
16 Multiple
and Curvilinear Regression
603
16.1
Multiple Regression: Computation
604
16.2
Multiple Regression: Hypothesis Tests
614
16.3
Path Analysis and Structural Equation Modeling
625
16.4
Partial and Multiple Correlation
644
16.5
Selection of Independent Variables
649
16.6
Computation of Multiple Regression by Matrix Methods
656
16.7
Solving Anovas as Regression Problems:
General Linear Models
659
16.8
Analysis of Covariance (Ancova)
665
16.9
Curvilinear Regression
671
16.10
Effect Size, Power, and Sample Size in Multiple Regression
685
16.11
Advanced Topics in Regression and Correlation
694
17
Analysis of Frequencies
703
17.1
Introduction to Tests for Goodness of Fit
704
17.2
Single-Classification Tests for Goodness of Fit
714
17.3
Replicated Tests of Goodness of Fit
730
17.4
Tests of Independence: Two-Way Tables
739
17.5
Analysis of Three-Way Tables
758
17.6
Analysis of Proportions
773
17.7
Randomized Blocks for Frequency Data
793
17.8
Effect Sizes, Power, and Sample Sizes
801
18
Meta-Analysis and Miscellaneous Methods
817
18.1
Synthesis of Prior Research Results: Meta-Analysis
817
18.2
Tests for Randomness of Nominal Data: Runs Tests
841
18.3
Isotonic Regression
847
18.4
Application of Randomization Tests to Unconventional Statistics
850
18.5
The Mantel Test of Association Between Two Distance Matrices
852
18.6
The Future of Biometry: Data Analysis
859
Appendices
A. Mathematical Proofs
869
B. Introduction to Matrices
885
Bibliography
891
Author Index
909
Subject Index
915
|
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| bvnumber | BV023716729 |
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| discipline | Biologie |
| edition | 4. ed. |
| format | Book |
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| language | English |
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| spelling | Sokal, Robert R. 1926-2012 Verfasser (DE-588)135625106 aut Biometry the principles and practice of statistics in biological research Robert R. Sokal and F. James Rohlf 4. ed. New York Freeman 2012 XIX, 937 S. zahlr. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. 891 - 908. - Hier auch später erschienene, unveränderte Nachdrucke Biometrie (DE-588)4124925-2 gnd rswk-swf Biostatistik (DE-588)4729990-3 gnd rswk-swf 1\p (DE-588)4151278-9 Einführung gnd-content 2\p (DE-588)4123623-3 Lehrbuch gnd-content Biostatistik (DE-588)4729990-3 s DE-604 Biometrie (DE-588)4124925-2 s 3\p DE-604 Rohlf, F. James 1936- Verfasser (DE-588)172335442 aut Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017217294&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Sokal, Robert R. 1926-2012 Rohlf, F. James 1936- Biometry the principles and practice of statistics in biological research Biometrie (DE-588)4124925-2 gnd Biostatistik (DE-588)4729990-3 gnd |
| subject_GND | (DE-588)4124925-2 (DE-588)4729990-3 (DE-588)4151278-9 (DE-588)4123623-3 |
| title | Biometry the principles and practice of statistics in biological research |
| title_auth | Biometry the principles and practice of statistics in biological research |
| title_exact_search | Biometry the principles and practice of statistics in biological research |
| title_full | Biometry the principles and practice of statistics in biological research Robert R. Sokal and F. James Rohlf |
| title_fullStr | Biometry the principles and practice of statistics in biological research Robert R. Sokal and F. James Rohlf |
| title_full_unstemmed | Biometry the principles and practice of statistics in biological research Robert R. Sokal and F. James Rohlf |
| title_short | Biometry |
| title_sort | biometry the principles and practice of statistics in biological research |
| title_sub | the principles and practice of statistics in biological research |
| topic | Biometrie (DE-588)4124925-2 gnd Biostatistik (DE-588)4729990-3 gnd |
| topic_facet | Biometrie Biostatistik Einführung Lehrbuch |
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