Evidence-Based Statistics. Peter M. B. Cahusac

      

      Table of Contents

      1  Cover

      2  Acknowledgements

      3  About the Author

      4  About the Companion Site

      5  Introduction References

      6  1 The Evidence is the Evidence 1.1 Evidence-Based Statistics 1.2 Statistical Inference – The Basics 1.3 Effect Size – True If Huge! 1.4 Calculations 1.5 Summary of the Evidential Approach References Notes

      7  2 The Evidential Approach 2.1 Likelihood 2.2 Misleading and Weak Evidence 2.3 Adding More Data and Multiple Testing 2.4 Sequence of Calculations Using t 2.5 Likelihood Terminology 2.6 R Code for Chapter 2 2.7 Exercises References Notes

      8  3 Two Samples 3.1 Basics Using the t Distribution 3.2 Related Samples 3.3 Independent Samples 3.4 Calculation Simplification 3.5 If Variance Is Known, or Large Sample Size, Use z 3.6 Methodological and Pro Forma Analyses 3.7 Adding More Data 3.8 Estimating Sample Size 3.9 Differences in Variances 3.10 R Code For Chapter 3 3.11 Exercises References Notes

      9  4 ANOVA 4.1 Multiple Means 4.2 Example – Fitness 4.3 Factorial ANOVA 4.4 Alerting r² 4.5 Repeated Measures Designs 4.6 Exercise References Notes

      10  5 Correlation and Regression 5.1 Relationships Between Two Variables 5.2 Correlation 5.3 Regression 5.4 Logistic Regression 5.5 Exercises References Notes

      11  6 Categorical Data 6.1 Types of Categorical Data 6.2 Binomial 6.3 Poisson 6.4 Rate Ratios 6.5 One-Way Categorical Data 6.6 2 × 2 Contingency Tables 6.7 Larger Contingency Tables 6.8 Data That Fits a Hypothesis Too Well 6.9 Transformations of the Variable 6.10 Clinical Trials – A Tragedy in 3 Acts 6.11 R Code for Chapter 6 6.12 Exercises References Notes

      12  7 Nonparametric Analyses 7.1 So-Called ‘Distribution-Free’ Statistics 7.2 Hacking SM 7.3 One Sample and Related Samples 7.4 Independent Samples