DMS420 Statistical Analysis

Code DMS420
Name Statistical Analysis
Status Compulsory/Courses of Limited Choice
Level and type Post-graduate Studies, Professional
Field of study Mathematics and Statistics
Faculty
Academic staff Jolanta Goldšteine, Jegors Fjodorovs, Viktors Ajevskis
Credit points 3.0 (4.5 ECTS)
Parts 1
Annotation The course deals with decision-making methods based on the Neumann-Pearson fundamental lemma, Naumann classical concept, the fundamentals of optimal strategy choice for statistical hypothesis testing; formulation of decision-making problems using statistical uncertainty and risk; construct Bayesian decision-making procedures and minimax procedure at statistical uncertainty; decision making using probability theory and asymptotic methods for parameter estimation; to construct the regression line..
Goals and objectives
of the course in terms
of competences and skills
The course is designed to teach students practical methods of statistical decision making under uncertainty, generated by unknown probability low; to construct hypotheses testing criterion; to construct the confidence intervals for unknown parameters; to construct the regression line; to apply ANOVA test.
Learning outcomes
and assessment
Student who has successfully mastered the training course: * is able to analyze empirical data and to use the software tool EXCEL for constructing statistical functions, graphs and histograms; - A student must demonstrate mastering these techniques by successfully completing the laboratory written test.
*is able to use the software tool EXCEL for generation of random numbers and to apply this tool for numerical calculations of integrals by the Monte Carlo method; - On these topics a student must complete one homework, as well as to solve some exercises of the examination test.
* is able to find the characteristics of time series and to construct the confidence intervals for mean and variance; - On these topics a student must complete one homework.
*is able to use the software EXCEL data analysis tools t-test and F-test to test the parametrical hypothesis, Kolmogorova-Smirnova test and Chi-square test to perform contrast of empirical and theoretical means; - Student must demonstrate mastering these techniques by successfully completing the laboratory written test, as wellas to solve some exercises of the examination test.
* is able to use the software EXCEL variances analysis tool ANOVA to test significance of factor; - On these topics a student must complete one homework, as well as to solve some exercises of the examination test.
is able to construct the regression line and to test the Hypothesis on regression coefficients. - Knowledge and skills of a student are tested by control work and results of the examination test.
Course prerequisites Matemātika 101

[Extended course information PDF]