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Introductory Biological Statistics

Second Edition

 

Raymond E. Hampton and John E. Havel

 

A thorough grounding in statistics is necessary for a career in any experimental science, but many students find themselves intimidated by the subject. Hampton and Havel have written this text with these students in mind. While providing the theory and assumptions necessary for a deep understanding of statistics, they make it approachable and keep it relevant to the interests of biology students. Their examples and exercises show how to choose the appropriate statistical method for a particular hypothesis and how to execute that method using problems encountered by real-world biologists. The second edition has been ambitiously updated and reorganized, facilitating clearer connections between topics and improving clarity of those that are logically distinct. A wide range of descriptive and inferential methods is covered, including: normal, binomial, and Poisson frequency distributions; sampling distributions; one- and two-sample t-tests; the Mann-Whitney and Wilcoxon signed-ranks tests; ANOVA; randomized block and factorial designs; correlations and regression analysis; and the chi-square test and other analyses of frequencies. The accompanying CD contains large data sets (in both ASCII and Excel formats), allowing students and instructors to save time and focus on concepts rather than data entry.

Glover-Mitchell, An Introduction to Biostatistics

 

$31.95 list, 175 pages

10-digit ISBN: 1-57766-380-2

13-digit ISBN: 978-1-57766-380-5

© 2006

Instructor's Manual available

Quantity:

“The Second Edition seems just as good as the First Edition—better spacing, particularly with respect to chapter questions. I appreciate the CD with PowerPoint slides. I also appreciate the student price. Topics covered are extremely adequate.”     — Marilyn Mathis, Howard Payne University 

“I have spoken to my students and they say the book is easy for them to understand. The language is lucid, examples and diagrams are sufficient. This book goes a long way to make students who fear biostatistics want to study it. Thank you.”     — Joseph D’Silva, Norfolk State University 

“Excellent. I especially like the examples that differentiate when to use one test as opposed to another. The price is unbelievably low. Great value for the students.”  — Phillip Clem, University of Charleston 

“Concise yet comprehensive and substantive. Arms the students with the tools to make wise decisions.”   — Will R. Getz, Fort Valley State University 

“Now that we have a CD with data, it is more accessible. I believe this book has the lowest price ever when compared with laboratory manuals. I like it, I recommend it, and I use it.”  — Babu Patlolla, Alcorn State University 

“An excellent presentation. I have used the well-written text to rethink the experimental designs of my research plots and, more importantly, to examine alternative approaches to reporting data, analysis, and results.”      — John M. Fowler, New Mexico State University

“I’ve been waiting a long time for a revised edition of Ray Hampton’s book. Having used it continuously for my undergraduate introductory class in biostatistics since it was published in 1994, I am excited about and hopeful that the second edition will be as effective an exposition of introductory statistics as the original.”  — Dan Townsend, University of Scranton

“Dr. Havel has done an outstanding job of revising the book while retaining the elements of the original that I liked so much. . . . I want my students to do statistics beyond their time here at my institution, and having a good book that they will carry with them is important for that goal. The second edition of Introductory Biological Statistics is a book I feel will continue to be invaluable for that effort.”  — Marcy Brown-Marsden, University of Dallas 

 

Table of Contents

 

1. Some Basic Concepts

What Is Statistics? / Populations and Samples / Randomness / Independence / Other Types of Samples

2. Data Measurement and Management of Numbers

Variables and Data / Scales of Measurement / Data Management

3. Frequency Distributions and Graphic Presentation of Data

Frequency Distributions of Discrete Variables / Frequency Distributions of Continuous Variables / Histograms and Their Interpretation / Cumulative Frequency Distributions / Other Handy Graph Types

4. Descriptive Statistics: Measures of Central Tendency and Dispersion

Sample Statistics and Population Parameters / Measures of Central Tendency / Measures of Dispersion / Descriptive Statistics from a Computer / Visualizing the Location of the Mean and Standard Deviation

5. Probability and Discrete Probability Distributions

Probability and Probability Distributions / The Binomial Distribution / The Poisson Distribution

6. The Normal Distribution

The Normal Distribution and Its Properties / The Standard Normal Distribution and Z Scores / Testing for Normality / Normal Approximation of the Binomial Distribution / Discrete Variables and the Normal Distribution / Parametric and Nonparametric Statistics

7. Statistical Inference I: Estimation and Sampling Distributions

An Introduction to Statistical Inference / Estimating a Population Mean: The Central Limit Theorem / Estimating a Population Mean: Standard Error of the Mean / Confidence Interval of μ When σ is Known / Confidence Interval of μ When σ is Unknown: The t Distribution / Reporting a Sample Mean and Its Variation

8. Statistical Inference II: Hypothesis Testing and the One-Sample t-Test

Statistical Hypothesis Testing and the Scientific Method / Test of a Hypothesis Concerning a Single Population Mean: The One-Sample t-Test / One-Tailed and Two-Tailed Hypothesis Tests / Statistical Decision Making and Its Potential Errors / Steps in Testing a Hypothesis

9. Inferences Concerning Two Populations and Paired Comparisons

The t-Test for Two Independent Samples / Confidence Interval for the Difference between Two Population Means / A Nonparametric Test for Two Independent Samples: The Mann-Whitney Test / Tests for Two Related Samples / The Paired t-Test / Nonparametric Tests for Two Related Samples / Power of the Test: How Large a Sample Is Sufficient? / Review: Which Statistical Test Is Appropriate? / Comparisons of Variances from Two Key Samples

10. Inferences Concerning Multiple Populations: ANOVA

The Rationale of ANOVA: An Illustration / The Assumptions of ANOVA / Fixed-Effects ANOVA (Model I) / Testing the Assumptions of ANOVA / Remedies for Failed Assumptions

11. Other ANOVA Designs

The Randomized Block Design / The Factorial Design / The Friedman Test / Other ANOVA Designs

12. Modeling One Measurement Variable against Another: Regression Analysis

Regression versus Correlation / Simple Linear Regression Fundamentals / Estimating the Regression Function and the Regression Line / Calculating the Estimated Regression Equation / Testing the Significance of the Regression Equation / The Confidence Interval for β / The Coefficient of Determination (r2) / Predicting y from x / Dealing with Several Values of y for Each Value of x / Checking Assumptions and Remedies for Their Failure / Advanced Regression Techniques

13. Association between Two Measurement Variables: Correlation

The Pearson Correlation Coefficient / A Correlation Matrix / Nonparametric Correlation Analysis (Spearman’s r)

14. Analysis of Frequencies

The Chi-Square Goodness-of-Fit Test / The Chi-Square Test for Association / The Fisher Exact Probability Test / The McNemar Test for the Significance of Changes / Graphic Displays of Frequency Data

15. Choice of Tests and a View of Some Other Procedures

Choice of the Appropriate Statistical Test / Experimental Design / A View of Some Other Statistical Procedures