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Statistics and R – from (Uni) classes to a Dissertation, by a Cambridge Grad

Statistics provides a valuable framework for analysing data and formalising how to derive conclusions from it. It is based on a very mathematical fundament, but stretches out to out-of-the box methods available in every computer.

For whom:
- You have a School class in Statistics or R
- You are writing a BSc/MSc Dissertation and you are lost: for example, you have a questionnaire and you need to analyse the data in there to write your thesis.
- You have practicals or need Stats for work.

You can learn:
- If required, mathematical foundations, formulas and logic underlaying statistics
- What is a p-value, what do all these words like factor analysis, normal distribution and test ACTUALLY MEAN and WHY do we need those?
- How to import your dataset and analyse it with R.

Extra information

For R / any stats program, a laptop is required

Location

At student's location: Around Vienna, Austria
Online via webcam

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General info

Age:
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level:
Beginner
Intermediate
Advanced
Duration:
60 minutes
The class is taught in:English, German, Ukrainian, Russian

About Me

About me:
- Sciency dude with a high-achiever mindset – top education, top grades, long plans.
- Love to teach – 4 years of tutoring experience, 1.5 years of formal employment as teaching assistant.
- About to start my PhD in the beautiful Vienna.
- Play violin.

My teaching style:
- I don't answer questions, I ask: to ensure a student gets a proper understanding of a subject, I break down information in small chunks and questions until the person comes to the conclusion on their own.
- I don't make you remember, I make sure you truly understand: in order for any piece of information to be stored in the long memory, a high volume of neural contacts has to be formed and trained. This can only be done by two things: (1) regular revision (2) building additional neural connections by pinning the knowledge to the broader ideas and the underlying logic. The second is what I am particularly after.

Education

- University of Cambridge, MPhil (MSc) with distinctions in Computational Biology.
- University of Vienna, BSc with distinctions in Mathematics.
- A-Levels: A* Mathematics, A* Further Mathematics, A* Russian.

- University of Vienna, currently enrolled for MSc in Bioinformatics
- University of Vienna, done Introductory Courses for BSc Biology

Experience / Qualifications

Currently:
- Institute of Science and Technology Austria (ISTA): Research Assistant for Alex Bronstein
- Starting September: PhD in Mathematics and Applied Computer Science at Ista.

Teaching experience:
- Tutor and Teaching Assistant at the University of Vienna for 2 semesters. (official employment)
- Tutor and Project Manager at Maths+ (volunteer project at the University of Vienna for Ukrainian refugees. official payed employment)
For whom: - You have a University Class in Programming - You are at School/Uni and want to get better at coding - You have an assignment or need to write a program for your project but don't know where to start What you will learn: - How to think algorithmically - How to better use AI/ChatGPT for your coding - Leetcode
A Cambridge and UniVie Grad and a soon-to-start PhD student in Computer Science and Mathematics at ISTA to teach Maths, Stats, CS and/or Computational Biology/Programming modules. Ich spreche auch Deutsch und kenne mich mit dem Schulmaterial (z.B. Matura) und Modulen aus Uniprogramm (BSc Mathe auf Uniwien) aus. If your goal is not just to learn some formulas by heart, but to gain a deep insight into how mathematical topics are interconnected, or to get a hand at coding and how to think algorithmically to solve complex tasks – I am just the right fit for you or your child. Additionally, I am personally familiar with the British educational system – from A-Levels (3 x A*) to University (MSc/MPhil from Cambridge with distinctions).

Ask a question

Send a message explaining your needs and Volodymyr will reply soon:
The more detail, the better.
Ex. "Hi, when are you available to meet for a lesson?"

Availability of a typical week

(GMT -05:00) New York
MonTueWedThuFriSatSun
0              
1  Monday at 1:00  Tuesday at 1:00  Wednesday at 1:00  Thursday at 1:00  Friday at 1:00  Saturday at 1:00  Sunday at 1:00
2  Monday at 2:00  Tuesday at 2:00  Wednesday at 2:00  Thursday at 2:00  Friday at 2:00  Saturday at 2:00  Sunday at 2:00
3  Monday at 3:00  Tuesday at 3:00  Wednesday at 3:00  Thursday at 3:00  Friday at 3:00  Saturday at 3:00  Sunday at 3:00
4  Monday at 4:00  Tuesday at 4:00  Wednesday at 4:00  Thursday at 4:00  Friday at 4:00  Saturday at 4:00  Sunday at 4:00
5  Monday at 5:00  Tuesday at 5:00  Wednesday at 5:00  Thursday at 5:00  Friday at 5:00  Saturday at 5:00  Sunday at 5:00
6  Monday at 6:00  Tuesday at 6:00  Wednesday at 6:00  Thursday at 6:00  Friday at 6:00  Saturday at 6:00  Sunday at 6:00
7  Monday at 7:00  Tuesday at 7:00  Wednesday at 7:00  Thursday at 7:00  Friday at 7:00  Saturday at 7:00  Sunday at 7:00
8  Monday at 8:00  Tuesday at 8:00  Wednesday at 8:00  Thursday at 8:00  Friday at 8:00  Saturday at 8:00  Sunday at 8:00
9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00  Friday at 9:00  Saturday at 9:00  Sunday at 9:00
10  Monday at 10:00  Tuesday at 10:00  Wednesday at 10:00  Thursday at 10:00  Friday at 10:00  Saturday at 10:00  Sunday at 10:00
11  Monday at 11:00  Tuesday at 11:00  Wednesday at 11:00  Thursday at 11:00  Friday at 11:00  Saturday at 11:00  Sunday at 11:00
12  Monday at 12:00  Tuesday at 12:00  Wednesday at 12:00  Thursday at 12:00  Friday at 12:00  Saturday at 12:00  Sunday at 12:00
13  Monday at 13:00  Tuesday at 13:00  Wednesday at 13:00  Thursday at 13:00  Friday at 13:00  Saturday at 13:00  Sunday at 13:00
14  Monday at 14:00  Tuesday at 14:00  Wednesday at 14:00  Thursday at 14:00  Friday at 14:00  Saturday at 14:00  Sunday at 14:00
15  Monday at 15:00  Tuesday at 15:00  Wednesday at 15:00  Thursday at 15:00  Friday at 15:00  Saturday at 15:00  Sunday at 15:00
16  Monday at 16:00  Tuesday at 16:00  Wednesday at 16:00  Thursday at 16:00  Friday at 16:00  Saturday at 16:00  Sunday at 16:00
17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
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from £39.17Online via webcam
from £43.43At student's home

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

Online reputation

  • Instructor since December 2024
  • Phone number verified

Availability of a typical week

(GMT -05:00) New York
MonTueWedThuFriSatSun
0              
1  Monday at 1:00  Tuesday at 1:00  Wednesday at 1:00  Thursday at 1:00  Friday at 1:00  Saturday at 1:00  Sunday at 1:00
2  Monday at 2:00  Tuesday at 2:00  Wednesday at 2:00  Thursday at 2:00  Friday at 2:00  Saturday at 2:00  Sunday at 2:00
3  Monday at 3:00  Tuesday at 3:00  Wednesday at 3:00  Thursday at 3:00  Friday at 3:00  Saturday at 3:00  Sunday at 3:00
4  Monday at 4:00  Tuesday at 4:00  Wednesday at 4:00  Thursday at 4:00  Friday at 4:00  Saturday at 4:00  Sunday at 4:00
5  Monday at 5:00  Tuesday at 5:00  Wednesday at 5:00  Thursday at 5:00  Friday at 5:00  Saturday at 5:00  Sunday at 5:00
6  Monday at 6:00  Tuesday at 6:00  Wednesday at 6:00  Thursday at 6:00  Friday at 6:00  Saturday at 6:00  Sunday at 6:00
7  Monday at 7:00  Tuesday at 7:00  Wednesday at 7:00  Thursday at 7:00  Friday at 7:00  Saturday at 7:00  Sunday at 7:00
8  Monday at 8:00  Tuesday at 8:00  Wednesday at 8:00  Thursday at 8:00  Friday at 8:00  Saturday at 8:00  Sunday at 8:00
9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00  Friday at 9:00  Saturday at 9:00  Sunday at 9:00
10  Monday at 10:00  Tuesday at 10:00  Wednesday at 10:00  Thursday at 10:00  Friday at 10:00  Saturday at 10:00  Sunday at 10:00
11  Monday at 11:00  Tuesday at 11:00  Wednesday at 11:00  Thursday at 11:00  Friday at 11:00  Saturday at 11:00  Sunday at 11:00
12  Monday at 12:00  Tuesday at 12:00  Wednesday at 12:00  Thursday at 12:00  Friday at 12:00  Saturday at 12:00  Sunday at 12:00
13  Monday at 13:00  Tuesday at 13:00  Wednesday at 13:00  Thursday at 13:00  Friday at 13:00  Saturday at 13:00  Sunday at 13:00
14  Monday at 14:00  Tuesday at 14:00  Wednesday at 14:00  Thursday at 14:00  Friday at 14:00  Saturday at 14:00  Sunday at 14:00
15  Monday at 15:00  Tuesday at 15:00  Wednesday at 15:00  Thursday at 15:00  Friday at 15:00  Saturday at 15:00  Sunday at 15:00
16  Monday at 16:00  Tuesday at 16:00  Wednesday at 16:00  Thursday at 16:00  Friday at 16:00  Saturday at 16:00  Sunday at 16:00
17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
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from £39.17Online via webcam
from £43.43At student's home

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

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