Master
2024/2025![Learning Objectives](/f/src/global/i/edu/objectives.svg)
![Expected Learning Outcomes](/f/src/global/i/edu/results.svg)
![Course Contents](/f/src/global/i/edu/sections.svg)
![Assessment Elements](/f/src/global/i/edu/controls.svg)
![Interim Assessment](/f/src/global/i/edu/intermediate_certification.svg)
Introduction to Statistics
Type:
Compulsory course (Data Analytics and Social Statistics)
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:
distance learning
Online hours:
40
Open to:
students of one campus
Master’s programme:
Аналитика данных и прикладная статистика
Language:
English
ECTS credits:
3
Contact hours:
8
Course Syllabus
Abstract
This course is an introductory course in statistics. It is designed to familiarize graduate students with the general concepts of decriptive and inferential statistical concepts, with a focus on probality theory. The course devlves in to introduction to probability theory ans its relation with the statistics, covers topics of important probability distributions, descriptive statistics and graphical display, point estimation and confidence intervals, hypothesis testing, measuring relations between variables.
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
- Week 1 Introduction to Probability Theory
- Week 2 Important Probability Distributions
- Week 3. Descriptive Statistics and Graphical display
- Week 4. Point estimation and confidence intervals
- Week 5. Hypothesis Testing
- Week 6. Measuring relations between variables
Assessment Elements
- Graded quizzesGraded quizzes for every section of the course. Students will have 3 attempts for every graded quiz.
- Hypothesis testing taskThe assignment should follow the logic of hypothesis testing as it is presented in the theoretical materials of the course. One attempt will be given.
- Final exam testFinal test with tasks covering the materials of the course. Students will be given two attempts.
Interim Assessment
- 2024/2025 1st module0.35 * Final exam test + 0.6 * Graded quizzes + 0.05 * Hypothesis testing task