This beginner-friendly course introduces the fundamental concepts of probability theory and statistics, focusing on both descriptive and inferential methods. Designed for individuals with little to no prior experience in statistics, it serves as a foundation for further studies in data analysis across various fields, including bioinformatics. The curriculum emphasizes practical applications, enabling students to summarize data, make data-driven decisions, and understand the principles behind statistical inference. This course is particularly beneficial for those preparing to work with data in research, business, or public health contexts. Additionally, it serves as a key bridge course for applicants preparing for the upcoming OMICSS-25 Genome Bioinformatics Summer School.
Alisa Davtyan has a master’s degree in financial mathematics from Yerevan State University. Since 2022, she has been working as a Teaching Associate at the American University of Armenia for Machine Learning, Time Series Forecasting, and Statistics courses. Currently, she works as an Associate Data Scientist Researcher at the Orbeli Institute of Physiology. Her research focuses on studying the mechanism of long-term memory at the single-molecule level.
Upon completing this course, students will develop essential statistical skills applicable to various domains. The course consists of theoretical and practical parts. The theoretical aspects of the theory of probability and statistics are developed by Dr. Vahan Huroyan, and available in our Bioinformatics Guide. The practicals will be conducted in Python and will be based on the University of Michigan's course "Inferential Statistical Analysis with Python" on Coursera. Key topics include:
Descriptive Statistics: Understanding types of variables, common distributions, and methods to summarize data.
Probability Theory: Introduction to basic probability concepts and their applications.
Inferential Statistics: Constructing confidence intervals, performing hypothesis tests, and interpreting p-values.
Data Analysis with Python: Utilizing Python libraries such as Statsmodels, Pandas, and Seaborn for statistical analysis.
This course is tailored for beginners who want to acquire statistical skills for data analysis in various fields.
No prior knowledge of statistics is required, but a good command of English is necessary to successfully complete the course. Additionally, availability to attend lessons in person.
Location: Armenian Bioinformatics Institute, Ezras Hasratyan 7, Yerevan, Armenia
Start date: April 22
End date: May 9
Schedule: Twice a week - Tuesday, Thursday - 7:00-8:30pm
This course can be taken independently or as a bridge course to prepare for OMICSS-25 Summer School in Genome Bioinformatics. The fee for this course is 20,000 AMD. If you wish to combine it with the other bridge courses, including Introduction to Programming you can enroll with a reduced fee:
One course: 20,000 AMD
Two courses: 35,000 AMD (total)
Those who wish to enroll must complete the application form. The registration deadline is April 17th at 11:59 PM Yerevan time.
Should you have any questions, feel free to contact us via the following means:
