Data Collection Methods in Data Science

Data Collection Methods:

The choice of data collection methods depends on the research under study, the research design, and the information gathered about the variable. Broadly, the data collection methods can be classified into two main categories:

1. Primary Data Collection Methods:

The primary data are the first-hand data, collected by the researcher for the first time. It is original in nature. The researcher collects fresh data when the research problem is unique and no related research work is done by any other person. The results of the research are more accurate when the data is collected directly by the researcher but however, it is costly and time-consuming.

2. Secondary Data Collection Methods:

When the data is collected by someone else for his secondary data. Thus, secondary data is the second-hand data that is readily available from other sources. This data collection is used by researchers to analyse and understand current data without collecting new data. It provides insights into historical patterns, comparisons, and large-scale statistical analysis.

Importance of Data Collection:

1. Erroneous conclusions that squander resources.

2. Decisions that compromise public policy.

3. Incapacity to correctly respond to research inquiries.

4. Bringing harm to participants who are humans or animals.

5. Deceiving other researchers into pursuing futile research avenues.

6. The study’s inability to be replicated and validated.