dc.contributor.author |
Ngunyi, Anthony |
|
dc.contributor.author |
Thomas Mageto |
|
dc.contributor.author |
Stella Mutahi |
|
dc.date.accessioned |
2021-05-27T09:41:38Z |
|
dc.date.available |
2021-05-27T09:41:38Z |
|
dc.date.issued |
2020-12 |
|
dc.identifier.citation |
tella Mutahi, Thomas Mageto, Antony Ngunyi. Inter-Arrival Time Modeling of Threshold Scores in Mathematics Among School Pupils; A Case of Acacia Crest School, Kenya. International Journal of Data Science and Analysis. Vol. 6, No. 6, 2020, pp. 213-219. doi: 10.11648/j.ijdsa.20200606.15 |
en_US |
dc.identifier.issn |
2575-1891 |
|
dc.identifier.uri |
10.11648/j.ijdsa.20200606.15 |
|
dc.identifier.uri |
http://repository.dkut.ac.ke:8080/xmlui/handle/123456789/4769 |
|
dc.description.abstract |
Mathematical literacy is the ability to use numbers to help solve real-world problems. It focuses on pupils' ability
to analyze, justify and communicate ideas effectively with regard to formulating, solving and interpreting Mathematical
problems in a variety of forms and situations. The study modeled above threshold scores in mathematics among school pupils
as an indicator for being mathematically literate. Modeling was on the inter-arrival times for pupils scoring above threshold
scores (Mathematics mean score) for a given sample of pupils in their mid and end of term examinations. The Poisson
distribution has been widely used as a statistical procedure for modeling inter-arrival times for count data outcomes. However,
for heavy-tailed inter-arrival times of successive outcomes, the Poisson distribution exhibits an empirical observational failure
thus setting up a framework for the use of other distributions that can handle such heavy-tailed data. The study used the
generalized Gumbel and Weibull inter-arrival time distributions which were assumed to nest the standard Poisson distribution
in which Weibull inter-arrival gave a better fit to the data. Data used was secondary data on pupil performance in Mathematics
in relation to other subjects from Acacia Crest School. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Science Publishing Group |
en_US |
dc.title |
Modeling Zero Inflation and Over-Dispersion in Domestic Package Insurance Claims Portfolio: A Case of Madison Insurance Company-Kenya |
en_US |
dc.type |
Article |
en_US |