Thanusha Jayawardana Lecturer in Statistics | MSc in Applied Statistics
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I am a qualified University Lecturer with a BSc (Hons) and an MSc in Applied Statistics. Whether you are a complete beginner or an undergraduate student facing difficulties with Statistics, I provide clear, step-by-step guidance tailored to your learning pace.

I specialize in making complex mathematical concepts easy to understand, even for those who find Statistics or Mathematics intimidating. My goal is to help you build a strong foundation from the very basics.

My Areas of Expertise Include:
Statistics for Beginners: Introduction to probability, descriptive statistics, and understanding data types.

Core & Advanced Statistics: Hypothesis testing, ANOVA, Regression analysis, and Multivariate techniques.

Data Science Foundations: Exploratory Data Analysis (EDA) and Statistical Inference.

Software Proficiency: Expert instruction in R Programming, SPSS, Minitab.

Why Choose My Sessions?

Beginner-Friendly: I break down difficult formulas into simple, logical steps that anyone can follow.

Practical Approach: I focus on real-world applications using modern software, moving beyond just theory.

I am dedicated to helping you achieve academic excellence and making your learning journey smooth and successful.

Subjects

  • Statistics Beginner-Expert

  • R programming Beginner-Expert

  • Minitab Beginner-Expert

  • SPSS (Statistical Package for the Social Sciences) Beginner-Expert


Experience

  • Lecturer (Visiting) (Jan, 2025Present) at University of Vocational Technology, Ratmalana, Sri Lanka
  • Instructor (Jan, 2023Jul, 2025) at General Sir John Kotalawela Defence University, Ratmalana, Sri Lanka

Education

  • MSc in Applied Statistics (Nov, 2022May, 2025) from University of Sri Jayawardenepura, Sri Lanka
  • BSc (Hons.) in Applied Statistics (Feb, 2017Jun, 2022) from South Eastern University of Sri Lanka, Oluvil

Fee details

    රු2,5006,000/hour (US$7.5818.18/hour)

    The fee depends on the complexity of the subject matter, the student's current academic level, and the specific requirements for exam preparation (e.g., intensive revision or software-based practical sessions).


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