THE ROLE OF SCIENCE AND TECHNOLOGY

THE ROLE OF STATISTICS IN SCIENCE AND TECHNOLOGY

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tatistics play a vital role in virtually all branches of science. Statistical methods are commonly used for analyzing experiment results, testing their significance and displaying the results accordingly.

• In order for a scientist to make an objective judgment as to whether or not a particular hypothesis can be established by a set of collected data, an objective method for either accepting, or rejecting, that hypothesis must be used. This is why, when collating these results, it is essential that statistics are included to ascertain the level or degree of accuracy in the hypothesis.

• Statistics can be used to explain qualitative, as well as the more easily decipher quantitative, results - that is to say it is possible for statistics to reveal elements of an experiment that would ordinarily be referred to by a characteristic value, rather than in a measurable way.


• The significance of statistical figures can be seen best when validating solid arguments or predictions out of hypotheses or conjectures that may seem overwhelming to a layman. It is far easier for the general public to understand the results of an experiment in greater clarity and detail if they have the simple reference point of numbers rather than scientific language, mathematics or equations.

• It could be argued that without the use, and advancements, of statistics and statistical research the empirical observations of today's scientists and inventors would be far less accurate and progressive. We all benefit from the developments and improvements in science that have been made to our day-to-day life, most of the time taking for granted what has been achieved with the aid of statistics.

Statistics are very important in science as well as technology for a number of reasons.

• Research

There are various research methods that use statistics to record their results, especially when it comes to experiments in the field of science. Once a number of experiments have been carried out, statistics will show a certain result. Then, scientists can accumulate all the statistics from each test to identify if there are any differences or changes over time. It is important to have statistics because it is the simple and stand-out way of representing a result.

• Significance

Statistics are a single number or a collection of numbers that show the importance of a certain change or development. In terms of technology this is important because statistics can show what the current trends are in terms of various technologies and the development of them. It is also good market research for companies that are creating various devices because statistics from areas around the country can help identify what the best device is to move forward with.

• Predictions

The value of statistics is strong because they can serve as predictions as well as probabilities in certain trends. This is especially the case in scientific experiments and studies because within a lot of scientific research it is about trial and error and what reactions work best. If there are professionals working towards substances for medical use, statistics can identify what works best.

Statistics plays a critical role in any modern use of technology in science and industry. Statistical concepts and methods are developed and applied in industries for various problems – for example, in order to monitor the quality of products, to plan effective and efficient designs to improve standards, to test and analyze the quality of items produced, and to accept (reject) conforming (nonconforming) units produced. The increased attention paid to these problems, and accompanying new statistical methodologies, has created an active and valuable new area of research and application-industrial statistics. The principal aim of the series is to sponsor publications addressing one or more of these critical information needs.

Publications in the series will contain statistical information that is accessible to an interdisciplinary audience: carefully organized authoritative presentations, numerous illustrative examples based on current practice, reliable methods, realistic data sets, and discussions of select new emerging methods and their application potential.

Principal Topic Areas

Life Testing * Reliability * Quality Monitoring * Quality Management * Quality Control * Time Series with Applications * Decision Theory * Survival Analysis * Prediction and Tolerance Analysis * Multivariate Statistical Methods * Nondestructive Testing * Accelerated Testing * Signal Processing * Design of Experiments * Computer Methods for Quality * Manufacturing * Software Reliability * Neural Networks

The series includes professional expository monographs, advanced textbooks, handbooks, general references, thematic compilations of applications/case studies and carefully edited survey books.

Readership

The publications will appeal to a broad interdisciplinary readership in applied statistics, industrial statistics, quality control, manufacturing, applied reliability, and general quality improvement methods. Graduates, researchers, and practitioners in industry and academia will find the publications accessible presentations and useful resources.