Biostatistical analysis
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1996
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| 245 | 1 | 0 | |a Biostatistical analysis |c Jerrold H. Zar |
| 250 | |a 3. ed. | ||
| 264 | 1 | |a Englewood Cliffs, NJ |b Prentice-Hall |c 1996 | |
| 300 | |a X, 662 S.: graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 490 | 0 | |a Prentice-Hall international editions. | |
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| _version_ | 1804125669043470336 |
|---|---|
| adam_text | BlOSTATISTICAL ANALYSIS
THIRD EDITION
JERROLD H ^AR
Department of Biological Sciences
Northern Illinois University
PRENTICE HALL
Upper Saddle River, New Jersey 07458
CONTENTS
PREFACE ix
INTRODUCTION 1
1 1 Types of Biological Data 2
1 2 Accuracy and Significant Figures S
POPULATIONS AND SAMPLES
2 1 Populations IS
2 2 Samples from Populations 16
MEASURES OF CENTRAL TENDENCY
3 1 The Arithmetic Mean 19
3 2 The Median 22
3 3 Other Quantiles 24
3 4 The Mode 26
1-3 Frequency Distributions 6
1 4 Cumulative Frequency Distributions 13
23 Random Sampling 16
2 4 Parameters and Statistics 17
3 5 Other Measures of Central Tendency 26
3 6 The Effect of Coding Data 27
Exercises 29
MEASURES OF DISPERSION AND VARIABILITY 31
4 1 The Range 31 , 4 6 The Coefficient of Variation-38
4 2 Dispersion Measured-with Quantiles 33
4 3 The Mean Deviation 33
4 4 The Variance 34
4 5 The Standard Deviation 37
5 PROBABILITIES 47
5 1 Counting Possible Outcomes 48
5 2 Permutations 49
5 3 Combinations 53
5 4 Sets 55
6 THE NORMAL DISTRIBUTION 65
6 1 Symmetry and Kurtosis 67
6 2 Proportions of a Normal Distribution 72
6 3 The Distribution of Means 75
4 7 Indices of Diversity 39
4 8 The Effect of Coding Data 42
Exercises 45
5 5 Probability of an Event 57
5 6 Adding Probabilities 58
5 7 Multiplying Probabilities 60
Exercises 62
6 4 Introduction to Statistical Hypothesis Testing
-65 Assessing Departures from Normality 86
Exercises 90
iv Contents
7 ONE-SAMPLE HYPOTHESES 93
7 1 Two-Tailed Hypotheses Concerning the Mean 93
7 2 One-Tailed Hypotheses Concerning the Mean 98
7 3 Confidence Limits for the Population Mean 100
7 4 Reporting Variability about [he Mean 102
7 5 Sample Size and Estimation of the Population
Mean 107
7 6 Power and Sample Size in Tests Concerning the
Mean 107
7 7 Sampling Finite Populations 110
7 8 Confidence Limits for the Population
Median 111
7 9 Hypotheses Concerning the Median 111
7 10 Confidence Limits for the Population
Variance 112
7 11 Hypotheses Concerning the Variance 113
7 12 Power and Sample Size in Tests Concerning
the Variance 113
7 13 Hypotheses Concerning the Coefficient of
Variation 115
7 14 Hypotheses Concerning Symmetry and
Kurtosis 116
Exercises 121
N
TWO-SAMPLE HYPOTHESES 123
8 1 Testing for Difference between Two Means 123
8 2 Confidence Limits for Population Means 130
8 3 Sample Size and Estimation of the Difference
between Two Population Means 132
8 4 Power and Sample Size in Tests for Difference
between Two Means 133
8 5 Testing for Difference between Two
Variances 137
8 6 Confidence Interval for the Population Variance
Ratio 140
8 7 Sample Size and Power in Tests for Difference
between Two Variances 141
8 8 Testing for Difference between Two Coefficients
of Variation 144
8 9 Nonparametric Statistical Methods 146
8 10 Two-Sample Rank Testing 147
8 11 Testing for Difference between Two
Medians 156
8 12 The Effect of Coding 156
8 13 Two-Sample Testing of Nominal-Scale
Data 157
8 14 Testing for Difference between Two Diversity
Indices 157
Exercises 159
PAIRED-SAMPLE HYPOTHESES 163
9 1 Testing Mean Difference 163
9 2 Confidence Limits for the Population Mean
Difference 166
9 3 Power and Sample Size in Paired-Sample Testing
of Means 166
9 4 Testing for the Difference between Variances
from Two Correlated Populations 166
9 5 Paired-Sample Testing by Ranks 167
9 6 Confidence Limits for the Population Median
Difference 171
9 7 Paired-Sample Testing of Nominal-Scale
Data 171
Exercises 177
MULTISAMPLE HYPOTHESES: THE ANALYSIS OF VARIANCE 179
10 1 Single-Factqr,A nalysis of Variance 180
10 2 Confidence Limits for Population Means
10 3 Power and Sample Size in Analysis of
Variance 191
10 4 Nonparametric Analysis of Variance 197
10 5 Testing for Difference among Several
Medians 202
10 6 Homogeneity of Variances 204
191 10 7 Homogeneity of Coefficients of Variation 206
10 8 The Effect of Coding 208
10 9 Multisample Testing for Nominal-Scale
Data 208
Exercises 208
MULTIPLE COMPARISONS 211
11 1 The Tukey Test 212
11 2 The Newman-Keuls Test 217
11 3 Confidence Intervals Following Multiple
Comparisons 218
11 4 Comparison of a Control Mean to Each Other
Group Mean 220
11 5 Schefft s Multiple Contrasts 222
11 6 Nonparametric Multiple Comparisons 226
11 7 Nonparametric Multiple Contrasts 229
11 8 Multiple Comparisons among Medians 229
11 9 Multiple Comparisons among Variances 231
Exercises 233
Contents
12 TWO-FACTOR ANALYSIS OF VARIANCE 235
12 1 Two-Factor Analysis of Variance with Equal
Replication 236
12 2 Two-Factor Analysis of Variance with Unequal
Replication 249
123 Two-Factor Analysis of Variance without
Replication 252
12 4 The Randomized Block Experimental
Design 254
12 5 Repeated-Measures Experimental Designs 259
12 6 Multiple Comparisons and Confidence Intervals
in Two-Factor Analysis of Variance 264
12 7 Power and Sample Size in Two-Factor Analysis
of Variance 265
13 DATA TRANSFORMATIONS 277
13 1 The Logarithmic Transformation 279
13 2 The Square Root Transformation 279
13 3 The Arcsine Transformation 282
12 8 Nonparametric Randomized Block or
Repeated-Measures Analysis of Variance 267
12 9 Multiple Comparisons for Nonparametric
Randomized Block or Repeated-Measures
Analysis of Variance 271
12 10 Dichotomous Nominal-Scale Data in
Randomized Blocks or from Repeated
Measures 272
12 11 Multiple Comparisons with Dichotomous
Randomized Block or Repeated-Measures
Data 274
12 12 Introduction to Analysis of Covariance 274
Exercises 275
13 4 Other Transformations 284
Exercises 284
14 MULTIWAY FACTORIAL ANALYSIS OF VARIANCE 285
14 1 Three-Factor Analysis of Variance 286
14 2 The Latin Square Experimental Design 289
14 3 Higher-Order Factorial Analysis of Variance 290
14 4 Blocked and Repeated-Measures Experimental
Designs 291
14 5 Factorial Analysis of Variance with Unequal
Replication 301
14 6 Multiple Comparisons and Confidence Intervals
in Multiway Analysis of Variance 302
14 7 Power and Sample Size in Multiway Analysis c
Variance 303
Exercises 303
307NESTED (HIERARCHICAL) ANALYSIS OF VARIANCE
15 1 Nesting within One Main Factor 309 15 4 Power and Sample Size in Nested Analysis of
15 2 Nesting in Factorial Experiments 312 Variance 315
153 Multiple Comparisons and Confidence Exercise 315
Intervals 314
16 8 Power and Sample Size in Regression 343
16 9 Regression through the Origin 344
16 10 Data Transformations in Regression 346
16 11 The Effect of Coding 350
Exercises 352
SIMPLE LINEAR REGRESSION 317
16 1 Regression vs Correlation 317
16 2 The Simple Linear Regression Equation 319
163 Testing the Significance of a Regression 326
16 4 Confidence-Intervals in Regression 330
16 5 Inverse Prediction 335
16 6 Interpretations of Regression Functions 337
16 7 Regression with Replication and Testing for
Linearity 338
COMPARING SIMPLE LINEAR REGRESSION EQUATIONS 353
17 1 Comparing Two Slopes 353 17 7 Multiple Comparisons among Elevations 366
17 2 Comparing Two Elevations 357 - 17 8 Multiple Comparisons of Points among
17 3 Comparing Points on Two Regression Regression Lines 367
Lines 361 17 9 An Overall Test for Coincidental
17 4 Comparing more than Two Slopes 362 Regressions 368
17 5 Comparing more than Two Elevations 365 Exercises 368
17 6 Multiple Comparisons among Slopes 365
vi Contents
SIMPLE LINEAR CORRELATION 371
18 1 The Correlation Coefficient 371
18 2 Hypotheses about the Correlation
Coefficient 375
18 3 Confidence Intervals for the Population
Correlation Coefficient 377
18 4 Power and Sample Size in Correlation 379
18 5 Comparing Two Correlation Coefficients 380
18 6 Power and Sample Size in Comparing Two
Correlation Coefficients 382
18 7 Comparing more than Two Correlation
Coefficients 384
18 8 Multiple Comparisons among Correlation
Coefficients 386
18 9 Rank Correlation 389
18 10 Weighted Rank Correlation 392
18 11 Correlation for Dichotomous Nominal-Scale
Data 395
18 12 Intraclass Correlation 398
18 13 Concordance Correlation 401
18 14 The Effect of Coding 404
Exercises 404
MULTIPLE REGRESSION AND CORRELATION 407
19 1 Intermediate Computational Steps 408
19 2 The Multiple Regression Equation 413
19 3 Analysis of Variance of Multiple Regression or
Correlation 415
19 4 Hypotheses Concerning Partial Regression
Coefficients 418
19 5 Standardized Partial Regression
Coefficients 420
19 6 Partial Correlation 420
19 7 Round-off Error and Coding Data 422
19 8 Selection of Independent Variables 423
19 9 Predicting ¥ Values 427
19 10 Testing Difference between Two Partial
Regression Coefficients 429
19 11 Dummy Variables 430
19 12 Interaction of Independent Variables 430
19 13 Comparing Multiple Regression
Equations 431
19 14 Multiple Regression through the Origin 433
19 15 Nonlinear Regression 434
19 16 Descriptive vs Predictive Models 436
19 17 Concordance: Rank Correlation among
Several Variables 437
Exercises 444
2 0 POLYNOMIAL REGRESSION 447
20 1 Polynomial Curve Fitting 447
20 2 Round-off Error and Coding Data 452
203 Quadratic Regression 452
Exercises 454
TESTING FOR GOODNESS OF FIT 457
21 1 Chi-Square Goodness of Fit 458
21 2 Chi-Square Goodness of Fit for More than Two
Categories 460
21 3 Subdividing Chi-Square Analyses 462
21 4 Chi-Square Correction for Continuity 464
21 5 Bias in Chi-Square Calculations 466
21 6 Heterogeneity Chi-Square 467
21 7 The Log-Likelihood Ratio 469
21 8 Kolmogorov-Smimov Goodness of Fit for
Discrete Data 471
21 9 Kolmogorov-Smirnov Goodness of Fit for
Continuous Data 474 ~
21 10 Sample Size Required for Kolmogorov-
Smirnov Goodness of Fit for Continuous
Data 477
Exercises 479
CONTINGENCY TABLES 483
22 1 Chi-Square Analysis of Contingency
Tables 485
22 2 Graphing Contingency Table Data 487
223 The 2x2 Contingency Table 488
22 4 Heterogeneity Testing of 2x2 Tables 497
22 5 Subdividing Contingency Tables 499
22 6 Bias in Chi-Square Contingency Table
Analyses 501
22 7 The Log-Likelihood Ratio for Contingency
Tables 502
22 8 Three-Dimensional Contingency Tables 503
22 9 Log-Linear Models for Multidimensional
Contingency Tables 509
Exercises 511
Contents vii
MORE ON DICHOTOMOUS VARIABLES
23 1 Binomial Probabilities 514
23 2 The Hypergeometric Distribution 520
233 Sampling a Binomial Population 521
23 4 Confidence Limits for Population
Proportions 524
23 5 Goodness of Fit for the Binomial
Distribution 527
23 6 The Binomial Test 530
23 7 The Sign Test 535
23 8 Power of the Binomial and Sign Tests 536
23 9 Confidence Interval for the Population
Median 539
23 10 The Fisher Exact Test 540
23 11 Comparing Two Proportions 552
23 12 Power and Sample Size in Comparing Two
Proportions 555
23 13 Comparing more than Two Proportions 559
23 14 Multiple Comparisons for Proportions 560
23 15 Trends among Proportions 562
Exercises 565
TESTING FOR RANDOMNESS 569
24 1 Poisson Probabilities 569
24 2 Confidence Limits for the Poisson Parameter 572
243 Goodness of Fit of the Poisson Distribution 573
24 4 The Binomial Test Revisited 576
24 5 Comparing Two Poisson Counts 580
24 6 Serial Randomness of Nominal-Scale Categories 581
24 7 Serial Randomness of Measurements: Parametric
Testing 584
24 8 Serial Randomness of Measurements:
Nonparametric Testing 585
Exercises 588
CIRCULAR DISTRIBUTIONS: DESCRIPTIVE STATISTICS
25 1 Data on a Circular Scale 591
25 2 Graphical Presentation of Circular Data 594
25 3 Sines and Cosines of Circular Data 596
25 4 The Mean Angle 598
25J Angular Dispersion 601
25 6 The Median and Modal Angles 603
25 7 Confidence Limits for the Population Mean and
Median Angles 604
25 8 Diametrically Bimodal Distributions 605
25 9 Second-Order Analysis: The Mean of Mean
Angles 606
25 10 Confidence Limits for the Second-Order Mean
Angle 609
Exercises 612
CIRCULAR DISTRIBUTIONS: HYPOTHESIS TESTING 615
26 1 Testing Significance of the Mean Angle:
Unimodal Distributions 615
26 2 Testing Significance of the Median Angle:
Omnibus Test 620
263 Testing Significance of the Median Angle:
Binomial Test 623
26 4 Testing Symmetry around the Median
Angle 623
26 5 Two-Sample and Multisample Testing of Mean
Angles 624
26 6 Nonparametric Two-Sample and Multisample
Testing of Angles 629
26 7 Two-Sample and Multisample Testing of
Median Angles 634
26 8 Two-Sample and Multisample Testing of
Angular Distances 634
26 9 Two-Sample and Multisample Testing of
Angular Dispersion 636
26 10 Parametric One-Sample Second-Order *
Analysis of Angles 637
26 11 Nonparametric One-Sample Second-Order
Analysis of Angles 638
26 12 Parametric Two-Sample Second-Order
Analysis of Angles 640
26 13 Nonparametric Two-Sample Second-Order
Analysis of Angles 642
26 14 Parametric Paired-Sample Testing with
Angles 644
26 15 Nonparametric Paired-Sample Testing with
Angles 646
26 16 Parametric Angular Correlation and
Regression 648
26 17 Nonparametric Angular Correlation 652
26 18 Goodness of Fit Testing for Circular
Distributions 653
26 19 Serial Randomness of Nominal-Scale
Categories on a Circle 657
Exercises 659
viii Contents
APPENDIX A ANALYSIS OF VARIANCE HYPOTHESIS TESTING App1
A I Determination of Appropriate F s and Degrees
of Freedom Appl
A 2 Two-Factor Analysis of Variance App5
A 3 Three-Factor Analysis of Variance App6
A 4 Nested Analysis of Variance App7
A 5 Split-Plot and Mixed Within-Subjects Analysis
of Variance App8
APPENDIX B STATISTICAL TABLES AND GRAPHS
Table B I Critical Values of Chi-Square
Distribution Appl3
Table B 2 Proportions of the Normal Curve
(One-Tailed) Appl7
Table B 3 Critical Values of the r Distribution Appl 8
Table B 4 Critical Values of the F
Distribution App20
Table B 5 Critical Values of the q
Distribution App56
Table B 6 Critical Values of q for the One-Tailed
Dunnett s Test App72
Table B 7 Critical Values of q for the Two-Tailed
Dunnett s Test App73
Table B 8 Critical Values of /max for the
Kolmogorov-Smirnov Goodness of Fit Test for
Discrete or Grouped Data App74
Table B 9 Critical Values of D for the Kolmogorov-
Smirnov Goodness of Fit Test for Continuous
Distributions App80
Table B 10 Critical Values of Ds for the ^-Corrected
Kolmogorov-Smirnov Goodness of Fit Test for
Continuous Distributions App84
Table B ll Critical Values of the Mann-Whitney U
Distribution App86
Table B 12 Critical Values of the Wilcoxon T
Distribution App99
Table B 13 Critical Values of the Kruskal-Wallis H
Distribution Appl02
Table B I4 Critical Values of the Friedman x?
Distribution Appl04
Table B I5 Critical Values of Q for Nonparametric
Multiple Comparison Testing Appl06
Table B 16 Critical Values of Q for Nonparametric
Multiple Comparison Testing with a
Control Appl07
Table B 17 Critical Values of the Correlation
Coefficient, r Appl08
Table B 18 Fisher s z Transformation for Correlation
Coefficients, r Appl 10
Table B 19 Correlation Coefficients, r,
Corresponding to Fisher s z Transformation Appl 12
ANSWERS TO EXERCISES Ans1
LITERATURE CITED L1
App11
Table B 20 Critical Values of the Spearman Rank
Correlation Coefficient, rs Appl 15
Table B 21 Critical Values of the Top-Down
Correlation Coefficient, rj Appl 17
Table B 22 Critical Values of the Symmetry
Measure, g Appl 18
Table B 23 Critical Values of the Kurtosis Measure,
g2 Appl20
Table B 24 The Arcsine Transformation, p Appl23
Table B 25 Proportions, p Corresponding to
Arcsine Transformations, p Appl 26
Table B 26a Binomial Coefficients,
nCx Appl28
Table B 26b Proportions of the Binomial
Distribution for p=q=05 Appl31
Table B 27 Critical Values of C for the Sign Test or
for the Binomial Test with p=05 Appl32
Table B 28 Critical Values for Fisher s Exact
Test Appl42
Table B 29 Critical Values for Runs Test Appl67
Table B 30 Critical Values of C for the Mean Square
• Successive Difference Test Appl74
Table B 31 Critical Values for the Runs Up and
Down Test Appl76
Table B32 Angular Deviation, s, As a Function of
Vector Length, r Appl78
Table B 33 Circular Standard Deviation, so, As a
Function of Vector Length, r Appl80
Table B 34 Critical Values of Rayleigh s z Appl82
Tabie B 35 Critical Values of u for the V Test of
Circular Uniformity Appl83
Table B36 Critical Values of m for the Hodges-Ajne
Test Appl84 -
Table B 37 Correction Factor, K, for the Watson
and Williams Test Appl86
Table B 38 Critical Values of Watson s U2 Appl 88
Table B 39 Critical Values of R for the Moore Test
of Circular Uniformity Appl91
Table B 40 Common Logarithms of Factorials Appl 92
Table B 41 Ten Thousand Random Digits Appl94
Figure B I Power and Sample Size in Analysis of
Variance Appl98
INDEX 11
|
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| id | DE-604.BV011173859 |
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| indexdate | 2024-07-09T18:05:14Z |
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| isbn | 013086398X |
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| spelling | Zar, Jerrold H. Verfasser aut Biostatistical analysis Jerrold H. Zar 3. ed. Englewood Cliffs, NJ Prentice-Hall 1996 X, 662 S.: graph. Darst. txt rdacontent n rdamedia nc rdacarrier Prentice-Hall international editions. Biométrie ram Biostatistik (DE-588)4729990-3 gnd rswk-swf Biostatistik (DE-588)4729990-3 s DE-604 HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007491926&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Zar, Jerrold H. Biostatistical analysis Biométrie ram Biostatistik (DE-588)4729990-3 gnd |
| subject_GND | (DE-588)4729990-3 |
| title | Biostatistical analysis |
| title_auth | Biostatistical analysis |
| title_exact_search | Biostatistical analysis |
| title_full | Biostatistical analysis Jerrold H. Zar |
| title_fullStr | Biostatistical analysis Jerrold H. Zar |
| title_full_unstemmed | Biostatistical analysis Jerrold H. Zar |
| title_short | Biostatistical analysis |
| title_sort | biostatistical analysis |
| topic | Biométrie ram Biostatistik (DE-588)4729990-3 gnd |
| topic_facet | Biométrie Biostatistik |
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