UNIT I: DATA AND DISTRIBUTIONS

1. Introduction

1.1 Statistics and the Life Sciences

1.2 Types of Evidence

1.3 Random Sampling

2. 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

3. 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)

4. 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

5. 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

6. Confidence Intervals

6.1 Statistical Estimation

6.2 Standard Error of the Mean

6.3 Confidence Interval for μ

6.4 Planning a Study to Estimate μ

6.5 Conditions for Validity of Estimation Methods

6.6 Comparing Two Means

6.7 Confidence Interval for (μ1 - μ2)

6.8 Perspective and Summary

7. 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

8. 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

9. 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

10. Categorical Data: Relationships

10.1 Introduction

10.2 The Chi-Square Test for the 2 × 2 Contingency Table

10.3 Independence and Association in the 2 × 2 Contingency Table

10.4 Fisher’s Exact Test

10.5 The r × k Contingency Table

10.6 Applicability of Methods

10.7 Confidence Interval for Difference Between Probabilities

10.8 Paired Data and 2 × 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

11. 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.