dc.description.abstract | This study investigates and analyses the factors influencing the distribution of educational facilities, and the variation in use of these facilities in Bondo Division, Siaya District. In distribution, factors such as transport network, population distribution, differential income levels and church influence have been examined: While under variation in use, factors such as accessibility, population density of school-age children and income level have been analyzed. In achieving the above-mentioned objectives, data from 1 primary and secondary sources were used. The former was collected from the field both by field observation and interviews using questionnaires. A total of 36 schools and 45 parents were sampled. In both distribution and variation in use of educational facilities, the various problems facing the primary schools have been highlighted and possible solutions have been proposed. Analysis of variation in use of educational facilities has been aided by the formulation of four hypotheses of the Null form which are tested using statistical techniques namely the simple correlation analysis, simple linear regression analysis and t-statistic which measures the degree of association between two sets of data. One hypothesis refers to the relation between the population of school-age children and the number of primary schools per sub¬ location. The second hypothesis refers to the relation between distance and time taken to get to the educational facilities in Bondo Division. The third seeks to test the relationship between the primary school enrolment and distance travelled from places of residence. The fourth hypothesis aims at finding out whether there is any significant relationship between the quality of the school and its enrollment. This last hypothesis is tested by the use of Spearman rank correlation statistic. Analysis of the distribution of educational facilities has been aided by the formulation of three hypothesis of the Null form which are tested using one statistical technique namely the Chi Square Test, which measures the difference between the observed and the expected frequencies of the given two sets of data. One hypothesis refers to the general distribution of primary schools in the study area i.e., whether they are uniformly distributed or not. The second seeks to test the relationship between transport network and the distribution of primary schools. The third hypothesis seeks to test relationship between income levels and the number of primary schools in each administration unit. Results of these hypothesis are well discussed in Chapter four. | |