

The concept of confidence intervals is general. You can calculate the 95% CI for almost any value you compute when you analyze data. We've already discussed the CI of a SD. Other confidence intervals computed by Prism include:
• The difference between two group means
•A proportion
•The ratio of two proportions
•The bestfit slope of linear regression
•The bestfit value of an EC50 determined by nonlinear regression
•The ratio of the median survival times of two groups
•The median of a set of values.
The concept is the same for all these cases. You collected data from a small sample and analyzed the data. The values you compute are 100% correct for that sample, but are affected by random scatter. A confidence interval tells you how precisely you have determined that value. Given certain assumptions (which we list with each analysis later in this book), you can be 95% sure that the 95% CI contains the true (population) value.
The fundamental idea of statistics is to analyze a sample of data, and make quantitative inferences about the population from which the data were sampled. Confidence intervals are the most straightforward way to do this.