Delivered at:: International Laboratory for Applied Network Research

Course type:: Compulsory course

When:: 1 year, 1 module

Instructor

Pavlova, Irina

Full Syllabus Ask Question

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 quizzes
Graded quizzes for every section of the course. Students will have 3 attempts for every graded quiz.
Hypothesis testing task
The 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 test
Final test with tasks covering the materials of the course. Students will be given two attempts.

Interim Assessment

2024/2025 1st module
0.35 * Final exam test + 0.6 * Graded quizzes + 0.05 * Hypothesis testing task

Bibliography

Recommended Core Bibliography

Agresti, A. (2017). Statistics: The Art and Science of Learning From Data, Global Edition. Pearson.

Recommended Additional Bibliography

James T. McClave, & Terry Sincich. (2013). Statistics: Pearson New International Edition. Pearson.

Authors

Pavlova Irina Anatolevna

Master’s Programme 'Data Analytics and Social Statistics'

Contacts

Introduction to Statistics