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kericho,
kenya
Det er i øjeblikket 11:17 AM her
Tilmeldt januar 14, 2021
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Benard T.
@tonuib08
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kericho,
kenya
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Genansættelsesrate
Statistician/Mathematician
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Erfaring
Assistant Lecturer (Staitistics)
sep. 2012 - Nuværende
I am a Statistician/Mathematician with MSc. (Statistics) degree and 10 years teaching experience at the university. I have also taught Mathematics and Business courses which include but not limited to Calculus, Algebra, Operations Research, Business Mathematics, Business Statistics, Quantitative Techniques, etc. I have experience in Data Entry and Analysis with R, MATLAB and SPSS. I also have experience in writing Mathematics projects/theses/dissertations using LATEX.
Uddannelse
MSc. (Statistics)
(3 år)
B.Ed (Science), Mathematics Major
(4 år)
Publikationer
On Markovian Queuing Models. (2014)
International Journal of Science and Research, Vol. 3 Issue 11; ISSN: 2319-7064, Pg. 93-96.
The ultimate objective of the analysis of queuing systems is to understand the behaviour of their underlying process so that
informed and intelligent decisions can be made by the management. In this study we apply a FIFO queuing model with unlimited customer population to catering data and estimate parameters for the same. A sensitivity analysis is the carried out to
evaluate stability of the system.
Estimation of Population Total using Model Based Approach. (2014))
International Journal of Scientific & Technology Research, Vol. 3, Issue 11, ISSN: 2277-8616
In this study we have explored an estimator for finite population total under the famous prediction approach. This approach has been compared with design-based approach using simple random sampling and stratified random sampling techniques. It is shown that the estimators under model based approach give better estimates than the estimators under design based approach both when using simple random sampling (s.r.s) and stratified random sampling.
A More Robust Random Effects Model for Disease Mapping. (2018))
American Journal of Theoretical and Applied Statistics. Vol. 7, No. 1, pp. 29-34. doi:0.11648
The most popular disease mapping model is the Besag-York-Molli´e model. Very often the spatially unstructured random effect is assumed to be normally distributed, an assumption that is restrictive in most practical situations. In this study, we investigate a more robust spatially unstructured random effect distribution by considering the Inverse Gaussian (IG) distribution. It was found out that that the IG distribution produce better results when the normality assumption is violated.
Spatio-Temporal Variation of HIV Infection in Kenya. (2018)
Open Journal of Statistics, 8, 811-830. https://doi.org/10.4236/ojs.2018.85053
Disease mapping models have found wide range of applications to epidemiology and public health. These models typically extend from GLM. In the spatio-temporal variation of HIV and AIDS in Kenya for the period 2013–2016, it was found out that INLA fit fairly complex models much faster than the popular McMC algorithms. The HIV and AIDS incidence rate for counties located in the Western region show significantly higher risks as compared to the other counties.
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