Math110BKK
Intro to Probability and Statistics
Faculty
Andrey Kechin
Master of Science fellow
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
This course introduces the core ideas of probability and statistics needed to understand data and uncertainty in real-world contexts. Students explore random events, probability models, and distributions before moving on to data collection, visualisation, and numerical summaries.
Key statistical concepts such as variability, correlation, sampling, and inference are presented through intuitive explanations and practical examples. Emphasis is placed on reasoning, interpretation, and avoiding common misconceptions, rather than heavy computation.
By the end of the course, learners will be able to analyse simple datasets, assess risk, and draw informed conclusions using probabilistic and statistical thinking.
Learning highlights
- By mastering the course, students gain the ability to think critically and write effective code with a deep understanding of:
- Probability theory
- Set and sample set theory
- Statistics, variations, covariations
- Connections between statistics and probability
Course outline
15 classes
Concepts of probability.
Sample space.
Properties of probability.
The continuity property of probability.
Finite sample space - combinatorial methods.
Main principles of counting.
Permutations and combinations.
The binomial theorem.
Conditional probability. Independent events.
The multiplicative Law of probability.
The Law of total probability.
Bayes Formula.
Distributions.
Skewness.
Random variables.
Convolutions.
Central limit theorem.
Hypothesis testing using the binomial distribution.
Significance levels.
Critical values and rejection regions.
One-tailed and two-tailed tests.
Hypothesis testing.
Cross validation.
Bayesian probabilities.
Chi-square test.
Efficient resampling.
Important discrete distributions.
Binomial distribution.
The Poisson distribution.
Basic concepts and formulas.
Midterm exam
Midterm exam
Continuous distributions.
Pareto distribution.
Normal distribution.
Normal probability plot.
Generating random numbers.
Estimations.
Estimation game.
Understanding errors.
Exponential distributions.
Confidence intervals.
Bayesian estimation.
Correlations.
Standard scores.
Covariance.
Correlation.
Least squares fit.
Correlation and causation.
The Poisson distribution.
Modelling with Poisson distribution.
Poisson approximation to the binomial distribution.
Hypothesis test for the mean of a Poisson distribution.
Applications of distributions in real problems.
Statistic in python.
Calculating the statistics in python and R.
Practical exercises.
General review
General review
Final exam
Final exam
Prerequisites
No special math skills required.
Methodology
The methodology is based on mixing PBL (problem-based learning) and IVL (interactive and visual learning) technologies. PBL is based on presenting real-world problems and guiding students to apply discrete math concepts like graph theory or combinatorics to solve them. IVL technology considers using visualisation tools in lecture studies.
Each class can be divided into three parts: Lection part/Active learning (discussion, Q&A)/Problem-solving part.
Students are encouraged to solve a task during the class that follows the homework. The homework is discussed at the beginning of the following class.
The Exams is splitted into two parts: theory and practice. 1/3rd of the score is theory 2/3 is practice.
Grading
Andrew graduated from Siberian Federal University and obtained the Master of Science degree in Physics in 2021.
The scientific interests are in biophysics, medicine, and modelling of real biology features in-silico. The master article is devoted to the quantum modelling of an Endothelial Growth Factor Receptor`s ligand as a target for positron emission tomography. Andrew is an awardee of a students olympiad and an active member of a math book translation team.
See full profileApply for this course
Intro to Probability and Statistics
by Andrey Kechin
Total hours
45 Hours
Dates
Mar 16 - Apr 03, 2026
Fee for single course
€1500
Fee for degree students
€750
How to secure your spot
Complete the form below to kickstart your application
Schedule your Harbour.Space interview
If successful, get ready to join us on campus
FAQ
Will I receive a certificate after completion?
Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.
Do I need a visa?
This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.
Can I get a discount?
Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.