Rent 9780024055019 | Statistics for Life Sciences | Myra L. Samuels @knetbooks.com

Summary Table of Contents

Statistics for the Life Sciences presents the key concepts of statistics as applied to the life sciences, while incorporating tools and themes of modern data analysis. The book emphasizes interpretation of results using real data which facilitates an understanding of statistics and data through the use of graphical data and analysis. It also provides a summary of methods in Chapter 13: "What to do When." The second edition of Statistics for the Life Sciences has been revised to include a number of new sections covering boxplots, probability trees, and probability plots. In addition, chapter 8 has been expanded to include a more complete discussion of issues in data collection, including observational studies vs. experiments, the placebo effect, the use of historical controls vs. active controls, and randomized response sampling. It now includes a new Chapter 10, which includes all of the chi-square test material as well as new sections on Fisher's exact test, McNemar's test, and relative risk and odds ratios. An essential statistics reference for professionals and scientists in biology, agronomy, medical and health sciences, nutrition, pharmacy, animal science, physical education, forestry, and other life sciences.

Preface

CHAPTER 1 INTRODUCTION

(10)

1.1 Statistics and the Life Sciences

(1)

... MORE

1.2 Examples and Overview

(9)

CHAPTER 2 DESCRIPTION OF SAMPLES AND POPULATIONS

(62)

2.1 Introduction

(2)

2.2 Frequency Distributions: Techniques for Data

(10)

2.3 Frequency Distributions: Shapes and Examples

(7)

2.4 Descriptive Statistics: Measures of Center

(6)

2.5 Measures of Dispersion: Methods

(6)

2.6 Measures of Dispersion: Interpretation and Comparison

(7)

2.7 Effect of Transformation of Variables (Optional)

(5)

2.8 Samples and Populations: Statistical Inference

(5)

2.9 Describing a Population

(7)

2.10 Perspective

(6)

CHAPTER 3 RANDOM SAMPLING, PROBABILITY, AND THE BINOMIAL DISTRIBUTION

(30)

3.1 Probability and the Life Sciences

(1)

3.2 Random Sampling

(8)

3.3 Introduction to Probability

(7)

3.4 The Binomial Distribution

(7)

3.5 Fitting a Binomial Distribution to Data (Optional)

(7)

CHAPTER 4 THE NORMAL DISTRIBUTION

103

(18)

4.1 Introduction

104

(3)

4.2 The Normal Curves

107

(1)

4.3 Areas Under a Normal Curve

108

(7)

4.4 The Continuity Correction (Optional)

115

(2)

4.5 Perspective

117

(4)

CHAPTER 5 SAMPLING DISTRIBUTIONS

121

(32)

5.1 Basic Ideas

122

(2)

5.2 Dichotomous Observations

124

(5)

5.3 Quantitative Observations

129

(12)

5.4 Illustration of the Central Limit Theorem (Optional)

141

(3)

5.5 The Normal Approximation to the Binomial Distribution (Optional)

144

(6)

5.6 Perspective

150

(3)

CHAPTER 6 ESTIMATION OF A POPULATION MEAN

153

(36)

6.1 Statistical Estimation

154

(1)

6.2 Confidence Interval for (XXX)

155

(10)

6.3 Interpreting and Reporting Summary Statistics

165

(10)

6.4 Planning a Study to Estimate (XXX)

175

(2)

6.5 Conditions for Validity of Estimation Methods

177

(6)

6.6 Perspective and Summary

183

(6)

CHAPTER 7 COMPARISON OF TWO INDEPENDENT SAMPLES

189

(76)

7.1 Introduction

190

(3)

7.2 Standard Error of (y(1) - y(2))

193

(7)

7.3 Confidence Interval for (Mu(1) - Mu(2))

200

(3)

7.4 Hypothesis Testing: The t Test

203

(11)

7.5 Further Discussion of the t Test

214

(5)

7.6 One-Tailed t Tests

219

(8)

7.7 More on Interpretation of Statistical Significance

227

(9)

7.8 Planning for Adequate Power (Optional)

236

(6)

7.9 Student's t: Assumptions and Summary

242

(4)

7.10 More on Principles of Testing Hypotheses

246

(3)

7.11 The Mann-Whitney Test

249

(9)

7.12 Perspective

258

(7)

CHAPTER 8 STATISTICAL PRINCIPLES OF DESIGN

265

(28)

8.1 Introduction

266

(1)

8.2 The Completely Randomized Design

267

(4)

8.3 Restricted Randomization: Blocking and Stratification

271

(4)

8.4 More on Randomization and Control

275

(7)

8.5 Levels of Replication

282

(4)

8.6 Observational Studies

286

(4)

8.7 Perspective

290

(3)

CHAPTER 9 COMPARISON OF TWO PAIRED SAMPLES

293

(34)

9.1 Introduction

294

(1)

9.2 The Paired-Sample t Test and Confidence Interval

294

(8)

9.3 The Paired Design

302

(6)

9.4 The Sign Test

308

(8)

9.5 Further Considerations in Paired Experiments

316

(3)

9.6 Perspective

319

(8)

CHAPTER 10 ANALYSIS OF CATEGORICAL DATA. I. CONFIDENCE INTERVALS AND GOODNESS-OF-FIT TESTS

327

(22)

10.1 Introduction

328

(1)

10.2 Confidence Interval for a Population Proportion

328

(5)

10.3 The Chi-Square Goodness-of-Fit Test

333

(8)

10.4 Applicability of Methods

341

(8)

CHAPTER 11 ANALYSIS OF CATEGORICAL DATA. II. CONTINGENCY TABLES

349

(40)

11.1 Introduction

350

(1)

11.2 The Chi-Square Test for the 2 (XXX) 2 Contingency Table

351

(7)

11.3 Independence and Association in the 2 (XXX) 2 Contingency Table

358

(13)

11.4 The r (XXX) k Contingency Table

371

(5)

11.5 Applicability of Methods

376

(3)

11.6 Confidence Interval for Difference Between Probabilities (Optional)

379

(3)

11.7 Summary of Chi-Square Tests

382

(7)

CHAPTER 12 COMPARING THE MEANS OF k INDEPENDENT SAMPLES

389

(44)

12.1 Introduction

390

(3)

12.2 The Basic Analysis of Variance

393

(11)

12.3 The Global F Test

404

(4)

12.4 Applicability of Methods

408

(1)

12.5 Linear Combinations of Means (Optional)

409

(12)

12.6 The Newman-Keuls Procedure (Optional)

421

(6)

12.7 Perspective

427

(6)

CHAPTER 13 LINEAR REGRESSION AND CORRELATION

433

(66)

13.1 Introduction

434

(3)

13.2 Basic Computations

437

(6)

13.3 The Fitted Regression Line

443

(10)

13.4 Parametric Interpretation of Regression: The Linear Model

453

(6)

13.5 Statistical Inference Concerning Beta(1)

459

(5)

13.6 The Correlation Coefficient

464

(11)

13.7 Guidelines for Interpreting Regression and Correlation

475

(11)

13.8 Perspective

486

(6)

13.9 Summary of Formulas

492

(7)

CHAPTER 14 MULTIPLICITY IN STATISTICAL INFERENCE

499

(12)

14.1 Introduction

500

(1)

14.2 Sources of Multiplicity

500

(3)

14.3 Guidelines for Controlling Multiplicity

504

(7)

CHAPTER APPENDICES

511

(22)

APPENDIX 2.1 Proof of the Computational Formula for the Standard Deviation

512

(1)

APPENDIX 2.2 More on Chebyshev's Rule

512

(2)

APPENDIX 3.1 Generating Pseudo-Random Numbers

514

(1)

APPENDIX 3.2 More on the Binomial Distribution Formula

515

(2)

APPENDIX 4.1 Areas of Indefinitely Extended Regions

517

(2)

APPENDIX 5.1 Relationship Between Central Limit Theorem and Normal Approximation to Binomial Distribution

519

(1)

APPENDIX 6.1 Significant Digits

520

(1)

APPENDIX 7.1 How Power Is Calculated

521

(2)

APPENDIX 7.2 More on the Mann-Whitney Test

523

(2)

APPENDIX 11.1 Conditional Probability and Independence

525

(1)

APPENDIX 12.1 More on the Newman-Keuls Procedure

526

(2)

APPENDIX 13.1 Derivation of Formulas for b(0) and b(1)

528

(3)

APPENDIX 13.2 Algebraic Relations Among Regression Quantities

531

(1)

APPENDIX 13.3 Calculations for Example 13.26

532

(1)

CHAPTER NOTES

533

(20)

STATISTICAL TABLES

553

(32)

TABLE 1 Random Digits

555

(4)

TABLE 2 Binomial Coefficients C(j)

559

(1)

TABLE 3 Areas Under the Normal Curve

560

(2)

TABLE 4 Critical Values of Student's t Distribution

562

(2)

TABLE 5 Number of Observations for Independent-Samples t Test

564

(2)

TABLE 6 Critical Values of U, the Mann-Whitney Statistic

566

(4)

TABLE 7 Critical Values of B for the Sign Test

570

(1)

TABLE 8 Critical Values of the Chi-Square Distribution

571

(1)

TABLE 9 Critical Values of the F Distribution

572

(10)

TABLE 10 Critical Constants for the Newman-Keuls Procedure

582

(3)

Answers to Selected Exercises

585

(8)

Index

593

(4)

Index of Examples

597

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