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Course Syllabus

Bachelor 2023/2024

Statistical Analysi

Type: Compulsory course (International Program 'International Relations and Global Studies')
Area of studies: International Relations
Delivered by: Faculty of World Economy and International Affairs
Where: Faculty of World Economy and International Affairs
When: 2 year, 3, 4 module
Mode of studies: offline
Open to: students of one campus
Language: English
ECTS credits: 3
Contact hours: 32

Course Syllabus

Full Syllabus

Abstract

Statistical Analysis is a one-semester course, its main objective is to provide students with a foundation of probability and basic methods of statistical data analysis. The course introduces the learner to the concepts of random events, conditional events, discrete and continuous random variables, their basic characteristics (expectation, variance, covariance, etc.), Central Limit Theorem, fundamentals of statistics and statistical theory, point and interval parameter estimation, hypothesis testing, linear regression. Learning statistical cocepts goes with training to calculate and try all the methods with the help of freely available software (R). The study of the course is based on the school course of mathematics (including the probability theory section).
Learning Objectives

Learning Objectives

  • The goal of this course is to provide students with foundations of probability theory and basic methods of statistical data analysis
Expected Learning Outcomes

Expected Learning Outcomes

  • Calculates any probability for Normal Distribution.
  • Be able to apply the Law of Large Numbers and the Central Limit Theorem.
  • Be able to analyze data using statistical methods and tools
  • Know the methods of interval estimation and T-statistics. Be able to work with different kinds of data
  • Able to use R programming language for statistical computations
  • Be able to conduct primary analysis of quantitative data - descriptive statistics and graphs
  • Know properties of normal distribution.
  • Students know how to solve problems related with probability, recognize probability distribution, and find its characteristics
  • Students are able to apply basic probabilistic formulas: the formula of total probability, Bayes’ formula
  • Students are able to compute probabilities for continuous random variables, their expectations, variance, covariance
  • Students are able to explain basic concepts of probability theory: random outcomes, random events, conditional probability, and independent random events
Course Contents

Course Contents

  • Probability theory
  • Normal Distribution and Central Limit Theorem
  • Mathematical Statistics
Assessment Elements

Assessment Elements

  • blocking Exam
    Solving problems with an oral defence
  • non-blocking Test
  • non-blocking Lab work test
  • non-blocking Activity
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.1 * Activity + 0.4 * Exam + 0.25 * Lab work test + 0.25 * Test
Bibliography

Bibliography

Recommended Core Bibliography

  • Modern mathematical statistics with applications, Devore, J. L., 2007

Recommended Additional Bibliography

  • Jan Ubøe. (2017). Introductory Statistics for Business and Economics. Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.spr.sptbec.978.3.319.70936.9