ABSTRACT
There is virtually no limit to the research that can be carried out on organizations. Areas as diverse as culture change, the factors associated with job satisfaction, team performance, marketing, organizational effectiveness, fairness, accounting practices and strategic management can be examined with a variety of research perspectives and using a broad range of research techniques. Very often this research involves measurement and, with it, the use of numbers. For example, it is possible to measure the job satisfaction of nurses and doctors by asking them how many aspects of the job they are happy with, or to measure the performance of hospitals by measuring how long patients take to recover from operations. With numerical measurement it is possible to collect information about large and representative samples of people, teams or organizations, and use this to look for important differences or associations between things, to make valuable predictions and to simplify complex relationships. By analysing and interpreting such numerical data, ideas can be confirmed or refuted, unexpected relationships can be discovered, theories can be developed and tested, and practical recommendations can be made. Numerical analysis is, therefore, of central importance to organizational research, and at the heart of numerical analysis is the discipline of statistics.
