Statistics And Statistics: The History And History Of Statistics

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First, ‘’Statistics is the study of the collections, analysis, interpretations, presentations, and organization of data.’’ It can be examined by a statistical population or in a statistical model to a traditional process starts. As populations "Each atom, forming a crystal" "All persons living in the country" or different topics. Statistical surveys and test all the data, including data collection deals with aspects of planning in terms of design. There are 2 main different strategies while data analysing; one is descriptive analysis which is summarizing data from using sample index, and the second is standart deviation which is creating conclusions from data. A standard statistical procedure two sets of statistical data, or includes …show more content…

At the beginning of the 19th century, it has expanded the scope of statistics collection and analysis of data should include discipline in general. Today, widespread government statistics, are employed in the business and the natural and social sciences About mathematical statistic found by Gerolamo Cardano in 17th century. Probability concept has already been examined by the medieval philosophers such as legal and Juan Caramuel, but mathematical probability theory, games of chance work appeared. In modern field of statistical studies are diveded in 3 stages. First, work of Francis Galton and Karl Pearson, who transformed statistics into mathematical discipline for using in analysis, not just in science, also in industry and politics as well. The second stage is between 1910’s and 1920’s was initiated by William Gosset, and reached its culmination in the insights of Ronald Fisher, who wrote the textbooks that were to define the academic discipline in universities around the all world. And the third stage, in particular, treatment and saw the last stage of enlargement of the previous development in the 1930’ …show more content…

• Some test methods and quality control like; ‘’Pass or fail’’ Mostly practical binary classification problems, the two groups are not symmetric and equal – rather than overall accuracy, the relative proportion of different types of interest. For example, in medical testing, false positive (detecting a disease when it is not present) is resulted differently from false negative (not detecting a disease when it is occured). Sometimes, classification tasks are petty. For instance; There are 100 fruits, some of them are banana, and others are apple, human eyes can able to see the difference between and pick which they want easly. ( If people doesnt have any health issues about their vision and capability to see in eyes). Generally people who use computer science has this problem.In order to automatically learn classification systems on the basis of training set of data containing observations whose category is already known and use the system to identify the category plotting of new observations. Some methods for commonly use in binary classifications are; Decision trees, Random forests, Bayesian networks, Support vector machines, Neural networks, Logistic

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