Dr. Gladys Gakenia Njoroge

Dr. Gladys Gakenia Njoroge

Lecturer

Email: gg.njoroge@chuka.ac.ke

Faculty of Science, Engineering and Technology

Department of Physical Sciences

Biography

Teaching

Outputs

Research/PhD

FIELD OF SPECIALISATION
Biostatistics

WORK EXPERIENCE
2012- 2017: Assistant Lecturer Chuka University
2017 – To date: Lecturer Chuka University

COMMUNITY SERVICE
BOM member Ruburi Secondary School, Motivating Girl child to pursue Mathematics

EDUCATION
Ph.D. in Biostatistics
Master of Science in Mathematical Statistics
BEd in Mathematics & Special Education

KEY RESEARCH PROJECTS
2015-2018: Optimization of herbal formulation for Diabetes Mellitus treatment

SCHOLALRLY PUBLICATIONS
1. Obare, D.M., Njoroge, G. G., Muraya, M. (2019).Analysis of Individual Loan Defaults Using Logit under Supervised Machine Learning Approach. Asian Journal of Probability of Probability and Statistics. Vol. 3 No. 4, pp 1-12. Doi:10.9734/ajpas/2019/v3i430100
2. Njoroge, G.G., Simbauni, J. A, Koske, J. (2017). An Optimal Split-Plot Design for Performing a Mixture-Process Experiment. Science Journal of Applied Mathematics and Statistics. 5(1):15-23.
3. Njoroge, G. G., Koske, J. & Simbauni, J. A. (2016). A Screening Experiment on a Diabetes Mellitus Herbal Formulation. American Journal of Theoretical and Applied Statistics. 5(6):387-394. doi: 10.11648/j.ajtas.20160506.18
4. Njoroge, G. G (2015). Estimation of Population Total Using Spline Functions. American Journal of Theoretical and Applied Statistics. Vol. 4, No. 5, pp. 396-403.doi: 10.11648/j.ajtas.20150405.20

RESEARCH INTRESTS: Biostatistics

POST GRADUATE TOPICS SUPERVISED
1.Modelling and application of response surface methodology for optimization of weight gain of eight weeks old kenbro served with pumpkin (Cucurbita pepo L.) seeds extract
2.Mathematical modeling of public sensitization initiatives on registration of persons in Kenya
3. Genome-wide association study of maize (Zea mays L.) using image-derived parameters.
Use of large scale phenotypic image data to model growth and development. A case of maize (Zea mays)

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