A Statistician and a movie lover.
Philomena Marfo
What I do
I am a statistician with a background in pure and applied mathematics. I am a researcher and teacher.
I also love teaching R programming for Statisticians, Tidyverse, Statistical inference, Statistical modelling and others.
Research areas are Climate Extremes, Bayesian Statistics, Meta-analysis and Time Series.Quote
The best project you can work on is yourself.
Work and Education
PhD Candidate
Kwame Nkrumah University of Science and Technology
2020-present
Teaching Assistant
African Institute for Mathematical Sciences (AIMS), Cameroon.
2018-2020
My work involved
- Preparing students in R programming
- Organising and conducting tutorials based on the courses delivered by world-leading lecturers
- Providing students with coaching and support for the courses on the agenda
- Coaching students throughout their end-of-the-year research thesis (Taught Master and Co-Op Masters)
- Delivering seminars on the mathematical concepts in some key R codes.
- Interacting with world-leading experts in Mathematical Sciences among which Nobel Prize Laureates to increase my own capacity in research and teaching of mathematical sciences.
Courses on the Agenda involves:
- Statistics Problem Solving
- Survival Analysis
- Statistical Finance
- Statistical Inference
- Statistical Climatology
- Computational Mathematics with SAGE
- Advanced-Data Analytics and Visualisation techniques with R
- Mathematical Modelling of Biological Systems
- Mathematical Population Genetics
- Data Analytics
- Geo-statistical models for public health
MPhil in Mathematical Statistics
Kwame Nkrumah University of Science and Technology
2016-2018
Thesis: The accuracy of effect size estimates under normals and contaminated normals in meta-analysis.
MSc in Mathematical Sciences
African Institute for Mathematical Sciences (AIMS-Ghana)
2015-2016
courses:
Skill Courses (Core)
- Mathematical Preliminaries and Latex
- Introduction to Python
- Mathematical Problem Solving
- Probability and Statistics with an Introduction to R
- Concepts in Physics and Physical Problem Solving
- Topics in Entrepreneurship and Professional Development
Review Courses (Elective)
- Modern Topics in Algebra
- Complex Analysis with Applications
- Complex Networks with Computations
- Functional Analysis
- Ordinary Differential Equations
- Combinatorial Algebraic Topology
- Algebraic Geometry
- Statistics
- Analytic Number Theory
- Dynamical Systems
- Pattern Recognition and Machine Learning
Research Phase
- Techniques of Meta-Analysis with an Application to the Introduction of Bt. Cotton in India.
BSc Mathematics
Kwame Nkrumah University of Science and Technology
2010-2014
Courses:
- Basic Physical Chemistry
- Communication Skills
- Introduction to Logic and Set Theory
- Electricity and Magnetism
- Information Technology
- Introduction to Pure Mathematics
- Introduction to Vector Analysis
- Introduction to Probability and Statistics
- Introduction to Discrete Mathematics
- Introduction to Algebra
- Differential Equations
- Elements of Economics
- Linear Algebra
- Mathematical Methods
- Probability and Statistics
- Literature in English
- Introduction to Analysis
- Introductory Programming for Mathematics
- Abstract Algebra
- Numerical Methods and Computations
- Complex Analysis
- Classical Fields
- Theoretical Mechanics
- Regression Analysis
- Topology
- Partial Differential Equations
- Time Series Analysis and Forecasting
- Application Development for Mathematics
- Real Functions
- Mathematical Economics
- Principles of Management
- Integral Equations
- Sample Survey Theory
- Stochastic Processes
- Introduction of Functional Analysis
Thesis: Information seeking behaviour of students (KNUST undergraduate students as a case study)
Publication and Research
The Accuracy of effect size estimates under normals and contaminated normals in meta-analysis.
This article evaluates the accuracy of effect-size estimates for some estimation procedures in meta-analysis. The dilemma of which effect-size estimate is suitable is still a problem in meta-analysis. Monte Carlo simulations were used to generate random variables from a normal distribution or contaminated normal distribution for primary studies. The primary studies were hypothesised to have equal variance under different population effect sizes. The primary studies were also hypothesised to have unequal variance. Meta-analysis was done on the simulated hypothesized-primary-studies. The effect sizes for the simulated design of the primary studies were estimated using Cohen's d, Hedges' g, Glass' △, Cliff's delta d and the Probability of Superiority. Their corresponding standard error and confidence interval were computed and a comparison of an efficient estimator was done using statistical bias, percentage error and confidence interval width. The statistical bias, percentage error and confidence interval width pointed to Probability of Superiority as an accurate effect size estimate under contaminated normal distribution, and Hedges' g as the most accurate effect size estimates compared to Cohen's d and Glass' △ when equal variance assumptions are violated. This study suggests that the accuracy of effect size estimates depends on the details of the primary studies included in the meta-analysis.
Research
- A meta-analysis of proportions: which transformation to use. (ongoing)
- The accuracy of effect size estimates under normals and contaminated normals in meta-analysis. (published)
- Techniques of meta-analysis with an application to the introduction of Bt. Cotton in India. (Masters degree)
- Information seeking behaviour of students; KNUST undergraduate students as a case study).
Research that I've helped students on.
- Modelling Run-off triangle and dependencies among them.
- Assessing students attitude to reading PIRLS 2011.
- Drug Resistance in P.vivax versus P.falciparum Malaria
- Using Quality Controlled Gridded Data (ENACTS) in Cameroon.
- Graphical Analysis of Survey Data.
- Evapotranspiration, PICSA and Crop Information.
- A Statistical Analysis of COVID-19: China, South Korea, Iran, the European countries, USA and
Canada Case Studies. - Modelling Climate Extremes.
- Modelling the Spread of COVID-19 in Africa.
Modelling Gestational Weight Gain trajectories using the Super Imposition Translation and Rotation growth model for predicting neonatal outcome
Photos & Videos
Take a look and enjoy!
At dinner with a friend.
What does it mean to be an African woman
This is a speech I gave on 8th March 2020 as part of the celebration for the international women's day. #eachforequal #IWD
Training of Trainers for Ghana Statistical Service.
Ghana 2021 Population and Housing Census
If It Means Crawling, Crawl But Keep Moving.
My STEM journey so far.
Click on the picture to read my journey so far.
https://winnienakiyingi.wordpress.com/2021/06/23/if-it-means-crawling-crawl-but-keep-moving-philomena-marfo/
Let's get intouch
© 2018