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Introductory Biological Statistics

ISBN: 9781577663805 | 1577663802
Edition: 2nd
Format: Paperback
Publisher: Waveland Pr Inc
Pub. Date: 8/22/2005

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SummaryTable of Contents
"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.
Prefacevi
Some Basic Concepts
1(6)
What Is Statistics?
1(1)
... MORE
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 A155(10)
Appendix B165(6)
Appendix C171(2)
Index173

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