Master
2023/2024
Introduction to Statistics
Type:
Compulsory course
Area of studies:
Applied Mathematics and Informatics
Delivered by:
International laboratory for Applied Network Research
Where:
Faculty of Social Sciences
When:
1 year, 1 module
Mode of studies:
offline
Open to:
students of one campus
Master’s programme:
Applied Statistics with Network Analysis
Language:
English
ECTS credits:
3
Contact hours:
28
Course Syllabus
Abstract
This course is an introductory course in network analysis, designed to familiarize graduate students with the general concepts and basic techniques of network analysis in sociological re-search, gain general knowledge of major theoretical concepts and methodological techniques used in social network analysis, and get some hands-on experience of collecting, analyzing, and mapping network data with SNA software. In addition, this course will provide ample opportu-nities to include network concepts in students’ master theses work.
Learning Objectives
- to give students the opportunity to get acquainted with the basic concepts of statistics
- to teach how to use statistical terms correctly and work with basic statistical concepts.
Expected Learning Outcomes
- be able to estimate the mean and variance of a sample
- be able to explain the rejection of statistical hypotheses
- be able to explain the use of different methods in relation to a certain measurement scale
- be able to formulate null and alternative statistical hypotheses
- know the difference between different measurement scales
- know which charts are suitable for which type of data
Course Contents
- The Where, Why, and How of Data Collection
- Graphs, Charts, and Tables—Describing Your Data
- Describing Data Using Numerical Measures
- Introduction to Probability
- Discrete Probability Distributions
- Introduction to Continuous Probability Distributions
- Introduction to Sampling Distributions
- Estimating Single Population Parameter
- Introduction to Hypothesis Testing
- Estimation and Hypothesis Testing for Two Population Parameters
- Hypothesis Tests and Estimation for Population Variances
- Analysis of Variance
