The purpose of statistical inference is to obtain information about a population form information contained in a sample.
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The importance of statistical modeling is obvious because we often need modelling for the purpose of prediction, to describe the phenomena and many procdures in statistics are based on assumption of a statistical model. Modeling is also important for statistical inference and make decision about population parameter. M. Yousaf Khan
The statistician compiles statistical information for the purpose of analysis. I want to be a statistician just like Dad when I grow up! Can you believe the distorted facts that alleged statistician came up with?
sers with a research interest are universities, consultants and government agencies. They generally understand something about statistical methodology and want to dig deeper into the facts and the statistical observations; they have an analytical purpose in inventing or explaining interrelations of causes and effects of different phenomena. In this field, official statistics are also used to assess a government's policies.One common point for all these users is their need to be able to trust the official information. They need to be confident that the results published are authoritative and unbiased. Producers of official statistics must maintain a reputation of professionalism and independence.The statistical system must be free from interference that could influence decisions on the choice of sources, methods used for data collection, the selection of results to be released as official, and the timing and form of dissemination. Statistical business processes should be transparent and follow international standards of good practice.Statistical programs are decided on an annual or multi-annual basis by governments in many countries. They also provide a way to judge the performance of the statistical system.
The purpose of warehousing is to provide a safe building to store goods. The purpose of distribution is a place to stock products to be redistributed to retailers, wholesalers, and consumers.
There is no difficulty in compiling employment statistics for firms in the quaternary sector. However, providing data on the number of quaternary jobs is made more difficult by the fact that some of those employed will be in firms whose main purpose is something else. For example, personnel employed in R&D in a pharmaceutical company may well be classified to the pharmaceutical sector. It would be necessary to collect information from sub-units in firms - for example, from pay-points.