Basic Principles of Statistics
Given a set of data, a number of measures can be derived that describe the set. These are called descriptive statistics and include values such as the mean and median, which show an average of the data, and the standard deviation, which describes how much variability is in the data.
In a clinical study, the results are never clear-cut. Theoretically, there is always a possibility that the observed data are the result of random chance. Using statistical methods, the researchers calculate the likelihood that the results are the result of chance. They determine in advance a threshold that this probability, abbreviated p, must reach, typically 5%, 1%, or 0.5% (expressed as p = .05, p =. 01, or p = .005, respectively). If p equals, say, 0.04, that means there is only a 4% probability that the results were due to chance, and therefore a 96% probability that a real correlation has been observed. A p value less than the threshold value is called a statistically significant result.
This type of analysis is called applied statistics. The pieces of information being analyzed may be raw data (such as blood test values) or they may be values derived from descriptive statistics.