EDA was initially promoted by few statisticians, but in recent years it has grown in acceptance. A large part of this growth is due to the availability of desktop computers and the explosion of data for which traditional statistics is just not suitable. Desktop computers have also made it possible to develop new graphical methods that support the EDA philosophy in strikingly effective fashion. Data Desk implements traditional statistics techniques that are suitable for data from planned experiments and sample surveys. These tools use innovative graphics in ways that are natural even for people who are not trained in statistics.
Most data arise as a byproduct of other activities.
For example, a business person may have data in a spreadsheet intended for tracking sales, data in a database for human resource management, or data that have been published by a government or trade organization. A researcher may collect data to sift a variety of alternatives, may want to look in a new way at data originally collected for a different purpose, or may want to check experiment data for errors or unexpected patterns. Data Desk is designed specifically for these functions. Traditional inferential statistics starts from a hypothesis, performs an experiment, and then tests the hypothesis. EDA starts instead from the data and asks what patterns, relationships, or trends they might hold.