ONLINE COURSE
Modern Statistical Thinking for Data Science and Analytics
A foundation to analyse data in scientifically objective way.
10
Classes
12
video lessons
15
scientific articles
25
exercises
COURSE CERTIFICATE
COURSE OVERVIEW
Statistical thinking is not only the key skill to analyse data in scientifically objective way, but also the key skill of the digital era. The course introduces the key statistical and non-statistical concepts to develop modern statistical thinking and it provides references for further learning.
WHAT IS MODERN STATISTICAL THINKING?
It is a thinking methodology of the modern statistical science, which enables us to analyse data in scientifically objective way.
WHAT IS MODERN STATISTICAL SCIENCE?
The development of modern statistical science goes back to 20th century with classical contributions such as Fisher’s randomisation (1925), Neyman’s modern concept of a confidence interval (1935) and Rubin’s Causal Model (Holland, 1986). These contributions had a significant impact on development of modern sampling theories, statistical inference and approaches for handling missing data.
Modern statistical science emphasizes the importance of carefully designed studies and for that reason requires from researchers to be familiar with statistical thinking that is founded on modern statistical science, i.e., modern statistical thinking.
what is this course about?
The course covers the key statistical and non-statistical concepts of a newly developed approach for developing modern statistical thinking (Kolar, 2019). The new approach defines statistical thinking as a conscious thought process that is based on statistical concepts of Modern Sampling theory, Missing data, understanding usefulness of Descriptive Statistics and challenges of conclusion-making in Inferential Statistics.
The central element of this new approach is causal thinking. Students get familiar with the science behind causal thinking as also fundamental principles to analyse causal relationships.
WHO IS THE COURSE FOR?
ABOUT THE FLOW oF tHE cOURSE
This is a fully self-paced course that consists of video lessons, gained understanding exercises, mini exercises, required reading material and a final assignment. The unique feature of this course is a regular feedback from the course instructor. The course instructor reviews gained understanding exercises and gets back to you with a feedback. This means that you are never alone on you learning journey.
ABOUT THE cOURSE MATERIAL
The material has been previously used for lectures, seminars and workshops at different venues, including University of Helsinki, Sigmund Freud University, Uppsala University and Tsinghua University. Currently, a similar version of this course is available to doctoral students at University of Helsinki. Look for future implementations here.
ABOUT INSTRUCTOR
Dr. Ana Kolar holds a PhD in Statistics. Her PhD advisor and statistical guru is one of the greatest statisticians of today – Emeritus Professor Dr. Donald B. Rubin from Harvard University. Ana is able to introduce and explain complex topics in a simple manner and she strives towards an educational approach that is based on experiential learning. Read more about Ana here.
COURSE OUTLINE
After completing this course, you will become familiar with the key statistical and non-statistical concepts required to develop modern statistical thinking – the thinking that will enable you to analyse data in scientifically objective way.
During the first two classes you learn about the modern statistical science and the key concepts of modern statistical statistical thinking. We explore the key statistical and methodological concepts required in empirical research to analyse data in scientifically objective way.
During the third and fourth class you learn about the science behind causal thinking and the impact that causal thinking has on designing studies, analysing data and conclusion-making. We introduce the concept of causality in statistical data analysis and explore how to analyse causal relationships. We look at the skills and attitudes that are required in order to fully master modern statistical thinking.
During Class 5 & 6 you become familiar with important role of sampling theory and understanding the impact that sampling strategies have on possibility to analyse data in scientifically objective way. You learn about the universe of missing data and missing data mechanisms – one of the key tools to be able to deal with biases.
During Class 7 & 8 we consolidate knowledge from previous classes and learn about importance of Descriptive Statistics tools in data analysis. You learn about circumstances that cause interpretations of Descriptive Statistics to be misleading and you learn how to assess quality of data using Descriptive statistics. We end these classes by exploring key factors for assessing Data Quality.
During Class 9 you learn what is behind the term Inferential Statistics and explore challenges and frequent misuses when using Inferential Statistics tools. Class 10 is a review class to ‘bring it all together’ and it is a class dedicated to the Final Assignment. Once you submit the Final Assignment, you are eligible to book a complimentary online session with the course instructor to receive feedback and to discuss additional questions they may have.
COMMON QUESTIONS
You can access the course material for 12 months from the date of enrolment or the course start date, whichever is later. An extension of this period may be available for a fee. Here’s why the fee is necessary:
By learning with us, you benefit from personalised guidance provided by the course instructor. Every time you submit an exercise to demonstrate your gained understandings, the exercise is reviewed by the course instructor. If you encounter challenges with exercises, the course instructor is there to provide assistance.
When you enrol in the course, a specific amount of time is set aside in the instructor’s schedule for interacting with you. This is why there is only a limited number of e-seats available. We can only accommodate a certain number of students at a time
Yes, you can cancel the course anytime during your Class 1 learning activities or before accessing material of Class 2, and you will get full refund. The cancellation needs to be done in writing by emailing to admin@tarastats.com within 30 days after enrolment or the official start of the course, whichever is later. Refunds will not be available after this time period as also not if you have already started with Class 2 learning activities.
The time required to complete this course may differ depending on your individual circumstances, such as studying full-time or part-time, your existing background in data analytics and statistics, and the depth of knowledge you wish to attain. With consistent effort, students can complete this course within 8 to 15 weeks.
The framework of this course curriculum provides a streamlined learning experience allowing you to attain learning outcomes that would typically require several years of commitment in traditional statistics classes or self-study through freely available online resources.
Unlike conventional courses, which may not accommodate your learning needs when it comes to your background knowledge, this online course offers a flexible format, enabling you to learn at your own capacity and pace, and receive feedback from course instructor whenever deepening understandings about challenging concepts.
In addition, this course curriculum integrates practical applications and real-world examples, ensuring that you not only grasp theoretical concepts but also understand how to apply them in various contexts. You will enhance your critical thinking skills and learn about skills and attitudes that are vital when attempting to analyse data in scientifically objective way.
Experiential learning prioritizes acquiring knowledge through direct experience, rather than passive reception. By actively engaging with the material, you have an opportunity to apply theoretical concepts to real-world scenarios, fostering a deeper understanding of the subject matter.
It is a hand-on approach that requires development of understanding by attending video lessons, studying scientific articles, and reflecting on acquired information. It is the reflection time that enforces learning and understandings. Consequently, the amount of knowledge you attain through this course depends on the amount of time you spend studying the material and reflecting on it. The more keen you are in learning, the more you will learn. The more time you put into studying the covered topics, the more understandings you will gain.
Reflection and self-assessment exercises are key components of the experiential learning approach. Throughout the course, you are required to articulate your gained understandings through reflective writing, analyzing your experiences when acquiring knowledge from video lessons and required readings. These gained understanding exercises stimulate deep and meaningful learning, helping you internalise the concepts and develop more profound understanding of the subject matter.
Because this course is about development of ‘thinking capacities’, regular written reflections play a vital role in your learning journey. With gained understanding exercises you articulate your thoughts, clarify understandings and develop critical thinking. Proficiency in the English language is important for effective participation in the course.
Also, keep in mind that this is a conceptual course which does not require a use of computer software, but rather a heavy use of ‘human mind software’.
If you have questions or are unsure whether this course is the right fit for you, please feel free to reach out by emailing to admin@tarastats.com.
Some thoughts
Equip yourself with the key skills of the digital era!
Discover the treasures of modern statistical thinking.
Are you ready to enrol?
This is a fully self-paced online course that includes interaction with the course instructor.
💎ENROLMENT IS OPEN💎
The course starts on the 12th of February 2025.
Online Course
Modern Statistical Thinking for Data Science and Analytics- 10 Classes & 12 Video lessons
- 15 Scientific articles & 25 Exercises
- Final Assignment & Regular feedback
- Online session with course instructor (45 min)
- COURSE CERTIFICATE
The fees are inclusive of 25.5% VAT.
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