Introductory Biological Statistics

by Hampton, Raymond E.; Havel, John E.

• ISBN13: 9781577663805
• ISBN10: 1577663802
• Edition: 2nd
• Format: Paperback
• Copyright: 2005-08-22
• Publisher: Waveland Pr Inc

Summary

"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."--BOOK JACKET.

Table of Contents

Preface	vi
Some Basic Concepts	1	(6)
What Is Statistics?	1	(1)
Populations and Samples	2	(1)
Randomness	3	(1)
Independence	4	(1)
Other Types of Samples	5	(2)
Key Terms	5	(1)
Exercises	5	(2)
Data Measurement and Management of Numbers	7	(6)
Variables and Data	7	(2)
Types of Variables	7	(1)
Significant Figures and Rounding Rules	8	(1)
Data and Their Representation	9	(1)
Scales of Measurement	9	(2)
The Nominal Scale	9	(1)
The Ordinal (Ranking) Scale	9	(1)
The Interval Scale and the Ratio Scale	10	(1)
Converting Data from One Scale to Another	10	(1)
Data Management	11	(2)
Key Terms	11	(1)
Exercises	11	(2)
Frequency Distributions and Graphic Presentation of Data	13	(6)
Frequency Distributions of Discrete Variables	13	(1)
Frequency Distributions of Continuous Variables	14	(1)
Histograms and Their Interpretation	15	(1)
Cumulative Frequency Distributions	16	(1)
Other Handy Graph Types	17	(2)
Key Terms	17	(1)
Exercises	17	(2)
Descriptive Statistics: Measures of Central Tendency and Dispersion	19	(10)
Sample Statistics and Population Parameters	19	(1)
Measures of Central Tendency	19	(3)
The Mode	19	(1)
The Median (θ, M)	20	(1)
The Mean (μ, x)	20	(1)
Positions of Mean, Median, and Mode in Symmetric and Skewed Distributions	20	(1)
Weighted Mean	21	(1)
Other Measures of Location	22	(1)
Measures of Dispersion	22	(3)
The Range	23	(1)
Interquartile Range	23	(1)
Standard Deviation (σ, s)	23	(2)
Coefficient of Variation	25	(1)
Descriptive Statistics from a Computer	25	(1)
Visualizing the Location of the Mean and Standard Deviation	25	(4)
Key Terms	26	(1)
Exercises	26	(3)
Probability and Discrete Probability Distributions	29	(10)
Probability and Probability Distributions	29	(2)
The Binomial Distribution	31	(4)
The Poisson Distribution	35	(4)
Key Terms	37	(1)
Exercises	37	(2)
The Normal Distribution	39	(10)
The Normal Distribution and Its Properties	39	(2)
The Standard Normal Distribution and Z Scores	41	(2)
Testing for Normality	43	(2)
Normal Approximation of the Binomial Distribution	45	(1)
Discrete Variables and the Normal Distribution	46	(1)
Parametric and Nonparametric Statistics	46	(3)
Key Terms	46	(1)
Exercises	47	(2)
Statistical Inference I: Estimation and Sampling Distributions	49	(10)
An Introduction to Statistical Inference	49	(1)
Estimating a Population Mean: The Central Limit Theorem	49	(2)
Estimating a Population Mean: Standard Error of the Mean	51	(1)
Confidence Interval of μ When σ is Known	52	(2)
Confidence Interval of μ When σ is Unknown: The t Distribution	54	(2)
Reporting a Sample Mean and Its Variation	56	(3)
Key Terms	56	(1)
Exercises	56	(3)
Statistical Inference II: Hypothesis Testing and the One-Sample t-Test	59	(8)
Statistical Hypothesis Testing and the Scientific Method	59	(1)
Test of a Hypothesis Concerning a Single Population Mean: The One-Sample t-Test	60	(2)
One-Tailed and Two-Tailed Hypothesis Tests	62	(1)
Statistical Decision Making and Its Potential Errors	63	(2)
Steps in Testing a Hypothesis	65	(2)
Key Terms	65	(1)
Exercises	66	(1)
Inferences Concerning Two Populations and Paired Comparisons	67	(16)
The t-Test for Two Independent Samples	67	(2)
Confidence Interval for the Difference between Two Population Means	69	(1)
A Nonparametric Test for Two Independent Samples: The Mann-Whitney Test	69	(2)
Tests for Two Related Samples	71	(1)
The Paired t-Test	72	(1)
Nonparametric Tests for Two Related Samples	73	(1)
The Sign Test	73	(1)
The Wilcoxon Signed-Ranks Test	74	(1)
Power of the Test: How Large a Sample is Sufficient?	74	(2)
Determining the Sample Size Needed to Detect a Minimum Effect	75	(1)
Determining Minimum Detectable Difference	76	(1)
Review: Which Statistical Test Is Appropriate?	76	(1)
Comparisons of Variances from Two Samples	77	(6)
Key Terms	77	(1)
Exercises	77	(6)
Inferences Concerning Multiple Populations: ANOVA	83	(18)
The Rationale of ANOVA: An Illustration	83	(2)
The Assumptions of ANOVA	85	(1)
Fixed-effects ANOVA (Model I)	86	(6)
Testing the Null Hypothesis That All Treatment Means Are Equal	87	(1)
Multiple Comparisons	88	(2)
Fixed-Effects ANOVA Using Survey Data	90	(1)
One-Way ANOVA Design with Random Effects	91	(1)
Testing the Assumptions of ANOVA	92	(2)
Remedies for Failed Assumptions	94	(7)
Transformations in ANOVA	94	(1)
Nonparametric Alternative to One-Way ANOVA: The Kruskal-Wallis Test	95	(1)
Key Terms	96	(1)
Exercises	96	(5)
Other ANOVA Designs	101	(12)
The Randomized Block Design	101	(3)
The Factorial Design	104	(3)
The Friedman Test	107	(1)
Other ANOVA Designs	108	(5)
Key Terms	108	(1)
Exercises	108	(5)
Modeling One Measurement Variable against Another: Regression Analysis	113	(16)
Regression versus Correlation	113	(3)
Simple Linear Regression Fundamentals	116	(1)
Estimating the Regression Function and the Regression Line	117	(2)
Calculating the Estimated Regression Equation	119	(1)
Testing the Significance of the Regression Equation	119	(2)
The Confidence Interval for β	121	(1)
The Coefficient of Determination (r2)	121	(1)
Predicting y from x	122	(1)
Dealing with Several Values of y for Each Value of x	123	(1)
Checking Assumptions and Remedies for their Failure	124	(1)
Advanced Regression Techniques	124	(5)
Key Terms	126	(1)
Exercises	126	(3)
Association between Two Measurement Variables: Correlation	129	(8)
The Pearson Correlation Coefficient	129	(2)
Testing the Significance of r	131	(1)
A Correlation Matrix	131	(1)
Nonparametric Correlation Analysis (Spearman's r)	132	(5)
Key Terms	134	(1)
Exercises	134	(3)
Analysis of Frequencies	137	(12)
The Chi-Square Goodness-of-Fit Test	137	(2)
The Chi-Square Test for Association	139	(2)
The Fisher Exact Probability Test	141	(1)
The McNemar Test for the Significance of Changes	142	(2)
Graphic Displays of Frequency Data	144	(5)
Key Terms	144	(1)
Exercises	144	(5)
Choice of Tests and a View of Some Other Procedures	149	(6)
Choice of the Appropriate Statistical Test	149	(1)
Experimental Design	150	(1)
A View of Some Other Statistical Procedures	150	(5)
Key Terms	153	(2)
Appendix A	155	(10)
Appendix B	165	(6)
Appendix C	171	(2)
Index	173