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Lecturer(s)
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Course content
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Random event and his probability, conditional probability. One-dimensional random variable. Two-dimensional and multiple random variable, function of random variable. Some important theoretical probability distributions. Limits theorems. Population and random sample, methods of descriptive statistics. Estimation theory. Testing hypotheses. Nonparametric methods. Linear regression. Correlation. Random number and its properties. Some methods of multivariate statistical analysis.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing)
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Learning outcomes
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The main goal of discipline is to develop acquaintance concerning basic ideas of the probability theory and fundamental statistical methods used for data processing in technical and economical practice and to show potentialities of available statistical software.
Student knows commonly used statistical methods (including multivariates methods), comprehends principles on which are this methods based, is able to choose a right method to solve a concrete problem. Is able to use available statistical software.
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Prerequisites
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Theory of probability and statistics - bachelor degree
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Assessment methods and criteria
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Home assignment evaluation
Given assignment confirms that a student has attended lessons to the extent required and fulfilled qualified requirements. Conditions for credit are: 1 seminary work. Form, contents and length of the exam are determined in accordance with Study and Examining Rules of University of Pardubice. The exam consists of two parts, a written test and a theoretical exam. Student passes successfully the written test as well as the theoretical part of the exam if he/she obtains at minimum 50% of possible points in each part.
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Recommended literature
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Arltová, M. Sbírka příkladů ze statistiky (A). Praha: VŠE, 1997.
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Cassella, G. Berger, R. L. Statistical inference Duxbury. ISBN 0-534-24312-6.
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Cyhelský, Lubomír. Elementární statistická analýza. Praha: Management Press, 1996. ISBN 80-85943-18-2.
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