Data collection and its Types
More than merely gathering data or composing a description, research is a highly specialized endeavour. It entails the focused collecting of data, which is then extensively analyzed to yield answers to research questions and assess the outcomes. Regardless of the subject matter, data collecting is the core of any research strategy. Every research project starts with a set of questions that must be addressed. Data collection is the act of carefully acquiring the desired information with the least amount of distortion possible so that the research can provide conclusions that are reliable and make sense.
Types of Data Collection:
There are two types of data:
- Primary Data
- Secondary Data
- Primary Data: Primary data is information that the researcher has personally collected. Since there are no earlier records of the data that the public may obtain, the researcher deliberately gathers this information. A variety of techniques, including surveys, interviews, focus groups, and more, can be used to gather primary data. Such information is regarded as being very trustworthy.
- Secondary Data: Secondary data is information that has been gathered and prepared by someone and is available to the general public. It is the information that the researcher gathered through earlier research and other resources. When primary information is subsequently used in another research project, it is referred to as secondary information. Official data, demographic information, departmental records, etc. are examples of secondary data. In comparison to using main data, using secondary data is less expensive and faster.
Qualitative Data: Qualitative data are mostly non-numerical and usually descriptive or nominal. This means the data collected are in the form of words and sentences. Often (not always), such data capture feelings, emotions, or subjective perceptions of something. Qualitative approaches aim to address the ‘how’ and ‘why’ of a program and tend to use unstructured methods of data collection to fully explore the topic. Qualitative questions are open-ended. Qualitative methods include focus groups, group discussions and interviews. Qualitative approaches are suitable for further exploring the effects and unintended consequences of a program. They are, however, expensive and time-consuming to implement. Additionally, the findings cannot be generalized to participants outside of the program and are only indicative of the group involved.
Qualitative data collection methods play an important role in impact evaluation by providing information useful to understand the processes behind observed results and assess changes in people’s perceptions of their well-being. Furthermore, qualitative methods can be used to improve the quality of survey-based quantitative evaluations by helping generate evaluation hypotheses; strengthening the design of survey questionnaires and expanding or clarifying quantitative evaluation findings.
These methods are characterized by the following attributes –
- they tend to be open-ended and have less structured protocols (i.e., researchers may change the data collection strategy by adding, refining, or dropping techniques or informants);
- they rely more heavily on interactive interviews; respondents may be interviewed several times to follow up on a particular issue, clarify concepts or check the reliability of data;
- they use triangulation to increase the credibility of their findings (i.e., researchers rely on multiple data collection methods to check the authenticity of their results);
Quantitative data is numerical and can be mathematically computed. Quantitative data measure uses different scales, which can be classified as nominal scale, ordinal scale, interval scale and ratio scale. Often (not always), such data includes measurements of something. Quantitative approaches address the ‘what’ of the program. They use a systematic standardized approach and employ methods such as surveys and asking questions. Quantitative approaches have the advantage that they are cheaper to implement, and are standardized so comparisons can be easily made and the size of the effect can usually be measured.
Quantitative approaches however are limited in their capacity for the investigation and explanation of similarities and unexpected differences. It is important to note that for peer-based programs quantitative data collection approaches often prove to be difficult to implement for agencies as a lack of necessary resources to ensure rigorous implementation of surveys and frequently experienced low participation and loss to follow-up rates are commonly experienced factors. The Quantitative data collection methods rely on random sampling and structured data collection instruments that fit diverse experiences into predetermined response categories. They produce results that are easy to summarize, compare, and generalize. If the intent is to generalize from the research participants to a larger population, the researcher will employ probability sampling to select participants.
Typical quantitative data gathering strategies include –
- Experiments/clinical trials.
- Observing and recording well-defined events (e.g., counting the number of patients waiting in an emergency at specified times of the day).
- Obtaining relevant data from management information systems.
- Administering surveys with closed-ended questions (e.g., face-to-face and telephone interviews, questionnaires etc).
- In quantitative research (survey research), interviews are more structured than in Qualitative research. In a structured interview, the researcher asks a standard set of questions and nothing more.
- Face-to-face interviews have a distinct advantage of enabling the researcher to establish rapport with potential participants and therefore gain their cooperation.
- Paper-pencil-questionnaires can be sent to a large number of people and saves the researcher time and money. People are more truthful while responding to the questionnaires regarding controversial issues in particular because their responses are anonymous.