Prague, Czech Republic

Probability, Mathematical Statistics and Econometry

Pravděpodobnost, matematická statistika a ekonometrie

Master's
Language: CzechStudies in Czech
Subject area: mathematics and statistics
Years of study: 2
University website: www.cuni.cz
Mathematical Statistics
Mathematical statistics is the application of mathematics to statistics, as opposed to techniques for collecting statistical data. Mathematical techniques which are used for this include mathematical analysis, linear algebra, stochastic analysis, differential equations, and measure-theoretic probability theory.
Probability
Probability is the measure of the likelihood that an event will occur. See glossary of probability and statistics. Probability is quantified as a number between 0 and 1, where, loosely speaking, 0 indicates impossibility and 1 indicates certainty. The higher the probability of an event, the more likely it is that the event will occur. A simple example is the tossing of a fair (unbiased) coin. Since the coin is fair, the two outcomes ("heads" and "tails") are both equally probable; the probability of "heads" equals the probability of "tails"; and since no other outcomes are possible, the probability of either "heads" or "tails" is 1/2 (which could also be written as 0.5 or 50%).
Statistics
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data. In applying statistics to, for example, a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal". Statistics deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments. See glossary of probability and statistics.
Statistics
Without the aid of statistics nothing like real medicine is possible.
Pierre Charles Alexandre Louis
Statistics
Statistics has been the most successful information science.
Those who ignore Statistics are condemned to reinvent it.
Attributed to Bradley Efron by Jerome H. Friedman (April 2001). "The Role of Statistics in the Data Revolution?". International Statistical Review 69: 5-10.
Statistics
In the 1930s English statistical theory was beginning to travel, with contributions from, amongst others, Hotelling and Snedecor in America and Darmois in France, but its home was still in England where there were four important centres: University College London, Rothamsted Experimental Station, Edinburgh University and Cambridge University with University College and Rothamsted far in the lead. Although Cambridge University was slow to adopt modern statistical theory, Cambridge men–Karl Pearson, Edmund Whittaker and Ronald Fisher–had put the other places on the statistical map. University College was the most established centre and its importance went back to 1893 when Karl Pearson, the professor of applied mathematics, first collaborated with Raphael Weldon, the professor of zoology on a subject they called “biometry.” There was a second surge in the “English statistical school” associated with R. A. Fisher who went to work at Rothamsted in 1919.
Aldrich, John (December 2009). "England and Continental Probability in the Inter-War Years". Electronic Journal for History of Probability and Statistics 5 (2): 5-6.
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