Statistics for the Life Sciences

UNIT I: DATA AND DISTRIBUTIONS1. Introduction1.1 Statistics and the Life Sciences1.2 Types of Evidence1.3 Random Sampling 2. Description of Samples and Populations2.1 Introduction2.2 Frequency Distributions2.3 Descriptive Statistics: Measures of Center2.4 Boxplots2.5 Relationships Between Variables2.6 Measures of Dispersion2.7 Effect of Transformation of Variables  2.8 Statistical Inference2.9 Perspective 3. Probability and the Binomial Distribution3.1 Probability and the Life Sciences3.2 Introduction to Probability3.3 Probability Rules (Optional)3.4 Density Curves3.5 Random Variables3.6 The Binomial Distribution3.7 Fitting a Binomial Distribution to Data (Optional) 4. The Normal Distribution4.1 Introduction4.2 The Normal Curves4.3 Areas under a Normal Curve4.4 Assessing Normality4.5 Perspective 5. Sampling Distributions5.1 Basic Ideas5.2 The Sample Mean5.3 Illustration of the Central Limit Theorem5.4 The Normal Approximation to the Binomial Distribution5.5 Perspective Unit I Highlights and Study UNIT II: INFERENCE FOR MEANS 6. Confidence Intervals6.1 Statistical Estimation6.2 Standard Error of the Mean6.3 Confidence Interval for  6.4 Planning a Study to Estimate  6.5 Conditions for Validity of Estimation Methods6.6 Comparing Two Means6.7 Confidence Interval for ( 1 -  2)6.8 Perspective and Summary 7. Comparison of Two Independent Samples7.1 Hypothesis Testing: The Randomization Test7.2 Hypothesis Testing: The t Test7.3 Further Discussion of the t Test7.4 Association and Causation7.5 One-Tailed t Tests7.6 More on Interpretation of Statistical Significance7.7 Planning for Adequate Power  7.8 Student\'s t: Conditions and Summary7.9 More on Principles of Testing Hypotheses7.10 The Wilcoxon-Mann-Whitney Test 8. Comparison of Paired Samples8.1 Introduction8.2 The Paired-Sample t Test and Confidence Interval8.3 The Paired Design8.4 The Sign Test8.5 The Wilcoxon Signed-Rank Test8.6 Perspective Unit II Highlights and Study UNIT III: INFERENCE FOR CATEGORICAL DATA9. Categorical Data: One-Sample Distributions9.1 Dichotomous Observations9.2 Confidence Interval for a Population Proportion9.3 Other Confidence Levels (Optional)9.4 Inference for Proportions: The Chi-Square Goodness-of-Fit Test9.5 Perspective and Summary 10. Categorical Data: Relationships10.1 Introduction10.2 The Chi-Square Test for the 2 x 2 Contingency Table10.3 Independence and Association in the 2 x 2 Contingency Table10.4 Fisher\'s Exact Test  10.5 The r x k Contingency Table10.6 Applicability of Methods10.7 Confidence Interval for Difference Between Probabilities10.8 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 RELATIONSHIPS11. Comparing the Means of Many Independent Samples11.1 Introduction11.2 The Basic One-Way Analysis of Variance11.3 The Analysis of Variance Model11.4 The Global F Test11.5 Applicability of Methods11.6 One-Way Randomized Blocks Design11.7 Two-Way ANOVA11.8 Linear Combinations of Means  11.9 Multiple Comparisons  11.10 Perspective 12. Linear Regression and Correlation12.1 Introduction12.2 The Correlation Coefficient12.3 The Fitted Regression Line12.4 Parametric Interpretation of Regression: The Linear Model12.5 Statistical Inference Concerning  112.6 Guidelines for Interpreting Regression and Correlation12.7 Precision in Prediction  12.8 Perspective12.9 Summary of Formulas Unit IV Highlights and Study 13. A Summary of Inference Methods13.1 Introduction13.2 Data Analysis Examples Chapter AppendicesChapter NotesStatistical TablesAnswers to Selected Exercises