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Curriculum subject

Statistical Analysis

Subject
Subject code RKE021
Subject name Statistical Analysis
Credit points 2.5 CP
Grading method Exam
Curriculum subject
Curriculum 2005 LI
Study year 2
Semester Spring semester
Subject type Mandatory
Subject loads
Lecture 16
Practice 24
General description
Overview of some Probability Distributions
Maximum Likelihood Estimators
Properties of Maximum Likelihood Estimators
Multivariate Normal Distribution
Confidence Intervals for Parameters of Normal Distribution
Gamma, Chi-squared, Student T and Fisher F Distributions
Testing Hypotheses about Parameters of Normal Distribution, t-Tests and F-Tests
Testing Simple Hypotheses
Most Powerful Test for Two Simple Hypotheses
Chi-squared Goodness-of-fit Test
Chi-squared Goodness-of-fit Test for Composite Hypotheses
Tests of Independence and Homogeneity
Kolmogorov-Smirnov Test
Simple Linear Regression
Multiple Linear Regression
General Linear Constraints in Multiple Linear Regression
General aim
This course provides an elementary introduction to statistical analysis with applications.
Aim
Student should be able to use basic statistical models; distributions; statistical estimation and testing; confidence intervals; and linear regression.
Form description
This course features a full set of lecture notes, as well as assignments. Individual work - studying the given notes, solving exercises, preparing for tests and exam.
Literature
1. DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics. 3rd ed. Boston, MA: Addison-Wesley, 2002.
2. Anderson D., Sweeney D., Williams T. Statistics for Busisness and Economics. West Publishing Company. 1996.
3. Lee C. F. Statistics for Business and Financial Economics. Lexington. 1993.
Current rounds
None
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