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Statistics as a subject may be divided in to descriptive statistics and inferential statistics. Descriptive statistics is that branch of statistics which deal with concepts and methods concerned with summarization and description of the important aspects of numerical data. The area of study relating to descriptive statistics consists of the condensation of data, their graphical displays and the computation of few numerical quantities that provide information about the center of the data and indicate the spread of the observations.
Descriptive statistics deals with methods of categorizing, summarizing, and presenting data in a convenient and informative way. One form of descriptive statistics uses graphical techniques, which allow statistics practitioner to present data in ways that make it easy for reader to extract useful information. Other shape of descriptive statistics uses mathematical methods to summarize data. One method we used frequently calculates the average or mean. In the same way we calculate average age of the employees of a company, we can compute the mean mark of last year’s statistics course. The authentic method we use depends on what precise information we would like to extract.
In given example, we can see at least three important pieces of information. The first is the “typical” mark. It is called measure of central location. The average is one such measure. “Median “is another measure of central location. Suppose average marks last year of student was 67. Is this enough information to reduce anxiety? The student would likely respond “no” because he would like to know whether most of marks were close to67 or were scattered far below or above average. The statistics student needs a measure of variability. The simplest such measure is range, which is calculated by subtracting the smallest number from largest. Suppose the large mark is 96 and smallest is 24. This provides little information. We need other measure. In particular we need to know how the marks are distributed between 24 and 96.
The best way to do this is to use a graphical technique, like to draw histogram.
Various other applications of statistics are biostatistics (relating to statistical analysis of the data phenomena pertaining to biological activities), econometrics (relating to statistical analysis pertaining to economic theories and relationships), actuarial sciences (relating to statistical analysis in insurance and risk related finance), operations research ( which utilizes statistics, mathematical models, and algorithms for generating optimal solutions for problems in operations management), quality control ( which makes use of statistical sampling for items of products to give assistance to process control), statistical mechanics ( which makes use of statistical tools for larger populations in relation to particle motion), business analytics ( which is related to applying of statistical methods to sets of larger business data), environmental statistics (which makes use of statistical tools and methods for environmental science), astrostatistics ( which makes of statistical analysis for gaining an understanding of astronomical data)
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