Chapter 9
Aiming for Accuracy and Precision
In This Chapter
Starting with accuracy and precision fundamentals
Boosting accuracy and precision
Determining standard errors for a variety of statistics
A very wise scientist once said, “A measurement whose accuracy is completely unknown has no use whatever.” Whenever you’re reporting a numerical result (and as a researcher, you report numerical results all the time), you must include, along with the numerical value, some indication of how good that value is. A good numeric result is both accurate and precise. In this chapter, I describe what accuracy and precision are, how you can improve the accuracy and precision of your results, and how you can express quantitatively just how precise your results are.
Beginning with the Basics of Accuracy and Precision
Before you read any further, make sure you’ve looked at the Statistical Estimation Theory section of Chapter 3, which gives an example introducing the concepts of accuracy and precision and the difference between them. In a nutshell: Accuracy refers to how close your numbers come to the true values; precision refers to how close your numbers come to each other. In this section, I ...
Get Biostatistics For Dummies now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.