Quantitative and Qualitative Research
Different methods exist for gathering data on Quantitative and qualitative research. In Qualitative research, the methods of data collection can be categorized into three broad categories including; interviews, Direct observation and document review. On the other hand, in Quantitative research, the main data gathering categories include; Experiments (clinical and lab trials), getting data from information systems, observing and recording well defined events and administering surveys with close-ended questions. However, the above methods can still be further subdivided into different subcategories so as to fit the research under survey.
Diverse data calls for specific methods of data collection. The most common means of collecting data include observation and recording, interviews and secondary sources. Depending on the data collected, different methods of analysis can be used that befits the data collected. For instance, through calculation of the mean, median and mode. This can be applied for both qualitative and Quantitative data.
Also, methods like counting, graphical representation, pie-charts, finding patterns in qualitative data and comparing results to previously determined goals and benchmarks. There are some computer packages that are used for data analysis (for example, SPSS), which can be used to analyze large amounts of data. A number of challenges may be experienced when collecting quantitative data. The most common and prevalent challenges include; resource constraints, time allocated for the data collection exercise may not be enough to get accurate data, infrastructural deficiencies and level of education. Some of the Quantitative data may require to be handled by experts in the specific field due to the complexity of the data under investigation.
For example clinical data, if collected by another person other that a clinical officer may not truly represent the expected outcome. When collecting Qualitative data, the challenges that can be envisaged would include; language barriers, cultural, religious or political diversity may lead to flawed information. The time frame set for the exercise can become a challenge in that if enough time is not set, then the data collected may not be representative of the whole scenario. Other challenges include; inadequacy of resources, weak organizational framework, Inability of relevant authorities to give relevant data on a timely basis, and little pride and pay in the job de-motivates the enumerators.