Fundamentals of Statistics for Data Science
Course code
ULP6613-25229
old course code
Course title in Estonian
Statistika alused andmeteaduses
Course title in English
Fundamentals of Statistics for Data Science
ECTS credits
8.0
Assessment form
Examination
lecturer of 2023/2024 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
lecturer of 2024/2025 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
The course gives the student fundamental statistical skills to approach more advanced technical issues of the area of data science and machine learning.
Brief description of the course
Introduction to statistics. Population vs sample. Basics of descriptive statistics. Measures of central tendency, asymmetry and variability. Statistical distributions. Estimators and estimates. Confidence intervals. Hypothesis testing and null models. Regression analysis.
Learning outcomes in the course
Upon completing the course the student:
- discusses the main topics and concepts associated with statistics;
- understands the fundamentals of statistics;
- knows how to work with and visualise different types of data;
- calculates measures of central tendency, asymmetry and variability, correlation and covariance;
- distinguishes and works with different types of distributions;
- estimates confidence intervals and performs hypothesis testing;
- makes data-driven decisions and understands the mechanics of regression analysis.
- discusses the main topics and concepts associated with statistics;
- understands the fundamentals of statistics;
- knows how to work with and visualise different types of data;
- calculates measures of central tendency, asymmetry and variability, correlation and covariance;
- distinguishes and works with different types of distributions;
- estimates confidence intervals and performs hypothesis testing;
- makes data-driven decisions and understands the mechanics of regression analysis.
Teacher
Nuno Fernando Oliveira Correia dos Santos
Study programmes containing that course