Statistics for the Life Sciences

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  • Edition: 2nd
  • Format: Hardcover
  • Copyright: 1/1/1999
  • Publisher: Pearson College Div
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For graduate or undergraduate courses in biology, agronomy, medical and health sciences, nutrition, pharmacy, animal science, physical education, forestry, and other life sciences. The style of Statistics for the Life Sciences is informal, uses only minimal mathematical notation, and makes extensive use of graphics and illustrations to teach the concepts. Only Elementary Algebra is required.

Table of Contents

Statistics and the Life Sciences
Examples and Overview
Description of Populations and Samples
Frequency Distributions: Techniques for Data
Frequency Distributions: Shapes and Examples
Descriptive Statistics: Measures of Center
Measures of Dispersion
Effect of Transformation of Variables (Optional)
Samples and Populations: Statistical Inference
Random Sampling, Probability, and the Binomial Distribution
Probability and the Life Sciences
Random Sampling
Introduction to Probability
Probability Trees
Density Curves
The Binomial Distribution
Fitting a Binomial Distribution to Data (Optional)
The Normal Distribution
The Normal Curves
Areas Under a Normal Curve
Assessing Normality
The Continuity Correction (Optional)
Sampling Distributions
Basic Ideas
Dichotomous Observations
Quantitative Observations
Illustration of the Central Limit Theorem (Optional)
The Normal Approximation to the Binomial Distribution (Optional)
Confidence Intervals
Statistical Estimation
Standard Error of the Mean
Confidence Interval for u
Planning a Study to Estimate u
Conditions for Validity of Estimation Methods
Confidence Interval for a Population Proportion
Perspective and Summary
Comparison of Two Independent Samples
Standard Error of (y1 - y2)
Confidence Interval for (u1 - u2)
Hypothesis Testing: The t-test
Further Discussion of the t-test
One-Tailed Tests
More on Interpretation of Statistical Significance
Planning for Adequate Power (Optional)
Student's t: Conditions and Summary
More on Principles of Testing Hypotheses
The Wilcoxon-Mann-Whitney Test
Statistical Principles of Design
Observational Studies
Restricted Randomization: Blocking and Stratification
Levels of Replication
Sampling Concerns (Optional)
Comparison of Two Paired Samples
The Paired-Sample t-Test and Confidence Interval
The Paired Design
The Sign Test
Further Considerations in Paired Experiments
Analysis of Categorical Data
Inference for Proportions: The Chi-Square Goodness-of-Fit Test
The Chi-Square Test for the 2 X 2 Contingency Table
Independence and Association in a 2 X 2 Contingency Table
Fisher's Exact Test (Optional)
The r x k Contingency Table
Applicability of Methods
Confidence Interval for a Difference Between Proportions
Paired Data and 2 X 2 Tables (Optional)
Relative Risks and the Odds Ratio (Optional)
Summary of Chi-Square Tests
Comparing the Means of k Independent Samples
The Basic Analysis of Variance
The Analysis of Variance Model (Optional)
The Global F Test
Applicability of Methods
Linear Combinations of Means (Optional)
Multiple Comparisons (Optional)
Linear Regression and Correlation
The Fitted Regression Line
Parametric Interpretation of Regression: The Linear Model
Statistical Inference Concerning B1
Summary of Formulas
A Summary of Inference Methods
Data Analysis Samples
Chapter Notes
Statistical Tables
Answers to Selected Exercises
Index of Examples
Table of Contents provided by Publisher. All Rights Reserved.

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