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Applied Statistics

Course Code:
11ASTA
Academic Degree:
doctoral
Study Programme:
Air Traffic Control and Management (P1041D040010)
language
czech, english flag
Intelligent Transport Systems (P1041D040011)
language
czech flag
Form of Study:
full-time and part-time
Type of Course:
optional
Course Completion:
exam
Supervisor:
doc. Ing. Evženie UGLICKICH, CSc.
v DB je chyba..
Supervising Department:
Department of Applied Mathematics (16111)
Abstract:
- Basic data processing: continuous and discrete data. Characteristics (mean, quantiles, covariance, correlation coefficient). Data visualization (histograms, bar and time plots, xy-charts) - Properties: Relations between variables, independence, correlation. - Linear and non-linear regression analysis and prediction: Prediction of future or missing values in measured data. - Distributional assumptions: Verification of the theoretical distribution of measured values. - Tests of hypotheses: Evaluation of a statistically significant difference in the results of scientific experiments when the assumptions of the data distribution are verified. - Hypothesis Tests: Evaluating a statistically significant difference in the results of scientific experiments without the assumption of data distribution - Hypothesis tests: Suitability of measured data for use in regression analysis - Hypothesis tests: Verification of the results of regression analysis. - Hypothesis Tests: Qualitative data processing. - Factor analysis: Reduction of the number of selected variables - Clustering: Data processing of multimodal nature. Selection of variables for clustering. - Clustering: basic clustering methods. - Clustering: Evaluating the difference of clusters.