Conventional statistical methods routinely miss differences among groups or associations among variables. These differences are detected by more modern techniques. Hundreds of journal articles have described the reasons why standard techniques are unsatisfactory. Nonetheless, simple and intuitive explanations are generally unavailable. Without assuming any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings easy to understand. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included.
Part One: Genesis of a Science*Derivation Curve*What Am I Holding*Least Squares*Quantifying Accuracy*Solving Bernoulli's Problem*Promoting Normality*Part II Exploiting Normality*Dealing with Small Samples Sizes*Correlation*Part Three: Dealing with Nonnormality*Revolution with a Whimper*Robust Methods*Bootstrap *Conclusion