Given Hapunda

161 Table 6: Multiple Comparisons Output of ANOVA Multiple Comparisons Dependent Variable: Malaria cases at baseline Bonferroni (I) project area (J) project area Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Mumbwa Chongwe -.61905 * .25237 .046 -1.2307 -.0074 Kafue -.04762 .25237 1.000 -.6593 .5641 Chongwe Mumbwa .61905 * .25237 .046 .0074 1.2307 Kafue .57143 .24247 .060 -.0163 1.1591 Kafue Mumbwa .04762 .25237 1.000 -.5641 .6593 Chongwe -.57143 .24247 .060 -1.1591 .0163 *. The mean difference is significant at the 0.05 level. The table above provides more information on how the residencies have been compared using the Bonferroni . The results in the output above show that only Mumbwa and Chongwe produced significant difference on the number of malaria cases reported ( p = .05). Qualitative Data Analysis Qualitative data analysis is the process of turning written data such as interviews and field notes into findings. Marshall & Ross (1990) define it as a search for general statements about relationships among categories of data. The qualitative test of a hypothesis, although subjective in the sense of relying upon observations of the researcher rather than quantitative statistics, can be equally as valid as the statistical test. A qualitative analysis of data uses the same processes of data organisation and evaluation as is found in quantitative analysis, albeit with non-numerical observations. This type of analysis has got no formulas that need to be applied. However, skill, knowledge and experience give critical insight on how that process can be done. This process needs the willingness to keep learning in order to get the best out of the data that is at hand. The willingness of working and learning while working on the data is cardinal in this process because there are no quick fixes when trying to make sense of the information in a much quicker way. Merriam (1998) describes this process of data analysis as a complex action of moving back and forth between data and concepts, between description and interpretation, using both inductive and deductive reasoning. Analysing data qualitatively has no fast-forward ways but requires patience on the part of those conducting the analyses. In qualitative analysis, it is encouraged that the analysis is done independently by different