Samuzahn Expected value and variance of 2D variable. Fundamentals of differential and integral calculus. Amazon Inspire Digital Educational Resources. Agatasqr added it Feb 03, Point estimation and the estimation of confidence intervals. Students jatematyczna use the tools in probability and statistics, survey design, the development and presentation of statistical material, the statistical inference in the analysis of the structure, methods for the analysis of the interdependence of mass and time series analysis.

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The module covers issues related to the theory of probability and mathematical statistics. Events and the probability of random events. Probability space. Definitions and properties of probability. The classical definition of probability.

Conditional probability and independence of of events. Probability of total and Bayes theorem. The distribution of a random variable. Discrete random variables displacements. Distributions of discrete random variable. Examples of discrete distributions: zero-one distribution, binomial distribution Bernoulli , the Poisson distribution, hypergeometric distribution. A continuous random variables. Examples of continuous distributions: uniform distribution, normal distribution, exponential distribution.

Functions of random variables. Numerical characteristics of random variables. Moments expected value, variance. Two-dimensional random variables and their characteristics. Limit theorems. Law of large numbers. Population, an attempt. Types of statistical characteristics and their measurement scales. The distribution and characteristics of the population in the sample.

Statistical series. The number of ordinary and cumulative. Graphical representation of data: histograms, line charts, pie, etc. The statistical parameters: measures of location, variability, asymmetry, concentration. Point estimation and the estimation of confidence intervals. Confidence intervals. Issues minimum size of the sample. Paasche-type indexes, indexes of the Laspeyres type and aggregate type Fisher index. Krysicki, J. Bartos, W. Dyczka, K. I, - PWN, Warszawa. Ostasiewicz, Z.

Rusnak, U. Siedlecka, - Statystyka. Sobczyk - Statystyka matematyczna, - Wydawnictwo Beck, Warszawa. Bobrowski D. Kot, J. Jakubowski, A. Chudzik, H. Markowicz, M. Mojsiewicz - Statystyka w zadaniach, cz. Middleton M. Students can use the tools in probability and statistics, survey design, the development and presentation of statistical material, the statistical inference in the analysis of the structure, methods for the analysis of the interdependence of mass and time series analysis.

Skip to main menu Skip to submenu Skip to content. Print syllabus. Choosen plan division: this week course term. Course descriptions are protected by copyright. Reset Password You are not logged in log in. Department of Power Electronics and Power Engineering. The syllabus - An introduction to probability theory - Elements of combinatorics. Issues minimum size of the sample - Verification of statistical hypotheses parametric and nonparametric tests of significance tests of significance - Methods of correlation and regression analysis analysis of selected aspects of the interdependence of mass - Methods of analysis of the dynamics of mass phenomena Types of time series, methods of testing a series of changes the dynamic extraction method development trend trend , fluctuations, indexes the individual and aggregate.

Bibliography used during lectures W. The student who completed the module. The ways of veryfing every mentioned outcome of teaching. Student is able to solve the task of probability and can make full development of statistical material, in particular, descriptive characteristics of the distributions measures: mean, variability, asymmetry, concentration , and statistical inference.

Assessment methods and assessment criteria:. Choosen plan division: this week course term see course schedule. Laboratory, 15 hours more information Lecture, 30 hours more information.

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