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Quantitative methods and modeling

  • Class 30
  • Practice 30
  • Independent work 60
Total 120

Course title

Quantitative methods and modeling

Lecture type

Obligatory

Course code

21-02-502

Semester

1

ECTS

4

Lecturers and associates

Course overview

Students will learn the theoretical and practical foundation of quantitative methods.

Students will learn to:
• Choose and apply appropriate methosd of descriptive statistics and interpret results.
• Choose and apply appropriate methods of parameter estimation and statistical tests and interpret results.
• Formulate research hypotheses, evaluate them using statistical methods, and summarize the results in a research paper.

This module will enable students to independently apply quantitative analysis and through examples and exercises develop the knowledge, understanding and skills of modelling realistic problems.

Content

General subject content:

• methosd of descriptive statistics and results interpretation
• methosd of regression analysis
• methods of parameter estimation, statistical tests and results interpretation
• Research hypotheses formulation, evaluate them using statistical methods, and summarize the results in a research paper.

Literature

Essential reading:
1. Albright, S. Ch., Winston, W. (2015). Business Analytics: Data Analysis and Decision Making, 5th Edition. Andover: CENGAGE Learning.

Minimal learning outcomes

  • Choose and apply appropriate method of univariate analysis and interpret the results
  • Choose and apply appropriate method of bivariate analysis and interpret the results
  • Estimate parameters of regression model, interpret regression coefficient, and use regression model for prediction
  • Choose and apply appropriate parameter estimation method and interpret the results
  • Choose and apply appropriate statistical test and interpret the results

Preferred learning outcomes

  • Apply and derive properties of measures of univariate analysis
  • Apply and derive properties of measures of association
  • Choose appropriate regression model and evaluate goodness-of-fit of the model
  • Apply parameter estimation methods in a research and present findings in a research paper
  • Formulate and test research hypotheses, and present findings in a research paper
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