Statistics for the life sciences
著者
書誌事項
Statistics for the life sciences
(Always learning)
Pearson, c2016
5th ed
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注記
Includes bibliographical references and indexes
内容説明・目次
内容説明
The Fifth Edition of Statistics for the Life Sciences uses authentic examples and exercises from a wide variety of life science domains to give statistical concepts personal relevance, enabling students to connect concepts with situations they will encounter outside the classroom. The emphasis on understanding ideas rather than memorizing formulas makes the text ideal for students studying a variety of scientific fields: animal science, agronomy, biology, forestry, health, medicine, nutrition, pharmacy, physical education, zoology and more. In the fifth edition, randomization tests have been moved to the fore to motivate the inference procedures introduced in the text. There are no prerequisites for the text except elementary algebra.
目次
Table of Contents UNIT I: DATA AND DISTRIBUTIONS
Introduction
1.1 Statistics and the Life Sciences
1.2 Types of Evidence
1.3 Random Sampling
Description of Samples and Populations
2.1 Introduction
2.2 Frequency Distributions
2.3 Descriptive Statistics: Measures of Center
2.4 Boxplots
2.5 Relationships Between Variables
2.6 Measures of Dispersion
2.7 Effect of Transformation of Variables
2.8 Statistical Inference
2.9 Perspective
Probability and the Binomial Distribution
3.1 Probability and the Life Sciences
3.2 Introduction to Probability
3.3 Probability Rules (Optional)
3.4 Density Curves
3.5 Random Variables
3.6 The Binomial Distribution
3.7 Fitting a Binomial Distribution to Data (Optional)
The Normal Distribution
4.1 Introduction
4.2 The Normal Curves
4.3 Areas under a Normal Curve
4.4 Assessing Normality
4.5 Perspective
Sampling Distributions
5.1 Basic Ideas
5.2 The Sample Mean
5.3 Illustration of the Central Limit Theorem
5.4 The Normal Approximation to the Binomial Distribution
5.5 Perspective
Unit I Highlights and Study
UNIT II: INFERENCE FOR MEANS
Confidence Intervals
6.1 Statistical Estimation
6.2 Standard Error of the Mean
6.3 Confidence Interval for
6.4 Planning a Study to Estimate
6.5 Conditions for Validity of Estimation Methods
6.6 Comparing Two Means
6.7 Confidence Interval for ( 1 - 2)
6.8 Perspective and Summary
Comparison of Two Independent Samples
7.1 Hypothesis Testing: The Randomization Test
7.2 Hypothesis Testing: The t Test
7.3 Further Discussion of the t Test
7.4 Association and Causation
7.5 One-Tailed t Tests
7.6 More on Interpretation of Statistical Significance
7.7 Planning for Adequate Power
7.8 Student's t: Conditions and Summary
7.9 More on Principles of Testing Hypotheses
7.10 The Wilcoxon-Mann-Whitney Test
Comparison of Paired Samples
8.1 Introduction
8.2 The Paired-Sample t Test and Confidence Interval
8.3 The Paired Design
8.4 The Sign Test
8.5 The Wilcoxon Signed-Rank Test
8.6 Perspective
Unit II Highlights and Study
UNIT III: INFERENCE FOR CATEGORICAL DATA
Categorical Data: One-Sample Distributions
9.1 Dichotomous Observations
9.2 Confidence Interval for a Population Proportion
9.3 Other Confidence Levels (Optional)
9.4 Inference for Proportions: The Chi-Square Goodness-of-Fit Test
9.5 Perspective and Summary
Categorical Data: Relationships
10.1 Introduction
10.2 The Chi-Square Test for the 2 x 2 Contingency Table
10.3 Independence and Association in the 2 x 2 Contingency Table
10.4 Fisher's Exact Test
10.5 The r x k Contingency Table
10.6 Applicability of Methods
10.7 Confidence Interval for Difference Between Probabilities
10.8 Paired Data and 2 x 2 Tables
10.9 Relative Risk and the Odds Ratio
10.10 Summary of Chi-Square Test
Unit III Highlights and Study
UNIT IV: MODELING RELATIONSHIPS
Comparing the Means of Many Independent Samples
11.1 Introduction
11.2 The Basic One-Way Analysis of Variance
11.3 The Analysis of Variance Model
11.4 The Global F Test
11.5 Applicability of Methods
11.6 One-Way Randomized Blocks Design
11.7 Two-Way ANOVA
11.8 Linear Combinations of Means
11.9 Multiple Comparisons
11.10 Perspective
Linear Regression and Correlation
12.1 Introduction
12.2 The Correlation Coefficient
12.3 The Fitted Regression Line
12.4 Parametric Interpretation of Regression: The Linear Model
12.5 Statistical Inference Concerning 1
12.6 Guidelines for Interpreting Regression and Correlation
12.7 Precision in Prediction
12.8 Perspective
12.9 Summary of Formulas
Unit IV Highlights and Study
A Summary of Inference Methods
13.1 Introduction
13.2 Data Analysis Examples
Chapter Appendices Chapter Notes Statistical Tables Answers to Selected Exercises
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