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Statistics and Mathematics for Advancing thinking and logic (University Based Teaching)

This is not your traditional math class! Rather than focusing on rote memorization or rigid formulas, this course emphasizes developing a deeper understanding of mathematical and statistical reasoning. Instead of simply teaching students how to calculate an average (mean), for instance, I will guide them toward discovering how to develop a value that they believe best represents an average. This reflective approach helps students think critically about the meaning and application of mathematical concepts, rather than just performing calculations.

The course prioritizes practical applications over theoretical repetition. You will engage with real-world case studies and utilize modern tools such as MATLAB, R, and Python to solve problems across fields like medicine, social sciences, and business. We will explore statistical reasoning, data analysis, and numerical algorithms, always with the goal of helping students connect these abstract concepts to professional and real-life scenarios.

By encouraging students to question, analyze, and understand the underlying logic of mathematical principles, the course fosters critical thinking and problem-solving skills. By the end, you will not only know how to perform calculations but also understand the "why" behind them, enabling you to apply mathematical reasoning effectively in academic and professional contexts.

Location

At student's location: Around Birmingham, United Kingdom
Online via webcam

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General info

Age:
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level:
Beginner
Intermediate
Advanced
Duration:
30 minutes
45 minutes
60 minutes
The class is taught in:English, Chinese

About Me

Hello! My name is Tim, and I am currently a Lecturer in Statistics and Psychometric at a UK University. My academic journey has equipped me with expertise in mathematics, statistics, and computational modelling, with a strong focus on their practical applications across various fields, especially in medicine and social sciences.

I hold a PhD in Computational Modelling from the University of Warwick, where my research centered around applying mathematical methods in interdisciplinary contexts. This has given me a deep understanding of both pure and applied mathematics, which I integrate into my teaching. I also hold an MSc in Physics from the Chinese University of Hong Kong, an MSc in Applied Mathematics from Imperial College London, and a BSc in Mathematics and Statistics (First Class Honours) from the University of Plymouth.

In addition to my academic qualifications, I have completed the PGCAP (FHEA Pathway) at the University of Liverpool. This has further refined my teaching practices, allowing me to create inclusive, student-centered learning environments that foster critical thinking and problem-solving.

Throughout my career, I have taught a wide range of subjects, from foundational mathematics to advanced statistics, at various academic levels. My experience includes developing course materials, delivering lectures and workshops, and guiding students through complex mathematical and statistical concepts using practical examples. I am proficient in mathematical software such as MATLAB, R, and Python, and I enjoy helping students navigate these tools to enhance their learning experience.

I am passionate about fostering a deeper understanding of mathematics and statistics, not just as technical skills, but as ways of thinking that can be applied across disciplines. I look forward to engaging with students and creating an interactive and meaningful learning journey.

I hold several academic degrees, including:

PhD in Computational Modelling, University of Warwick
MSc in Physics, Chinese University of Hong Kong
MSc in Applied Mathematics, Imperial College London
BSc in Mathematics and Statistics (First Honours), University of Plymouth
PGCAP (FHEA Pathway), University of Liverpool

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Availability of a typical week

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from £35Online via webcam
from £41At 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 September 2024
  • Google connected

Availability of a typical week

(GMT -05:00) New York
MonTueWedThuFriSatSun
0              
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2            Saturday at 2:00  Sunday at 2:00
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from £35Online via webcam
from £41At 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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