Whenever any research is conducted, it focuses mainly on two aspects: one is modeling of the situation, and the other is testing of the model in a real life scenario. The first half is referred to as the theory building, whereas the latter one is referred to as the theory testing. With the graduation of time, the latter part has gained enhanced importance in the community of the researchers. The main reason behind this is to replicate the same theoretical framework in several diversified contexts. With minor changes and modifications in the existing model, the same theoretical model can be tested across several contexts. This type of study is called “Empirical Study”. One of the major challenges of this type of study is the data collection.
Depending upon the type of study, required data can be classified into several categories. The broad classifications are described as per the following:
Time-series data: This is a particular category of data, which is collected for any variable over a period. Some specific trends and behavioral patterns are visible in this data. It is mainly used for studying any behavior or pattern over a period.
Cross-sectional data: This is a particular type of data, which is collected for several variables at any point of time. This data is majorly used for comparative analysis.
Panel data: This is a particular type of data, which is collected for several variables over a period. In short, it is a mix of time-series and cross-sectional data. This data is majorly used for time dependent comparative analysis and analyzing behavioral patterns across variables.
Categorical data: This type of data is mainly collected for explorative studies and the objectification of subjective variables. The variables are assigned a set of real numbers and are codified for analysis.
Scale data: This type of data is collected for both explorative and explanatory studies. The specialty of this data is that they do not denote any categories, but they signify the order of preference of the variables for any subject under consideration. They also objectify the set of subjective variables.
Given the set of data types, it is solely up to the way the researcher wants to present and analyze the data in the study. Falsification and mistakes in identification of data type while data collection may lead to rejection of the entire study.
With a view to helping researchers in the process of data collection, a number of organizations are present with their expertise. “phdbox.in” is one of the pioneers in the field of data collection for dissertation.
Data Collection for Research
Posted by admin in PhD Thesis
Whenever any research is conducted, it focuses mainly on two aspects: one is modeling of the situation, and the other is testing of the model in a real life scenario. The first half is referred to as the theory building, whereas the latter one is referred to as the theory testing. With the graduation of time, the latter part has gained enhanced importance in the community of the researchers. The main reason behind this is to replicate the same theoretical framework in several diversified contexts. With minor changes and modifications in the existing model, the same theoretical model can be tested across several contexts. This type of study is called “Empirical Study”. One of the major challenges of this type of study is the data collection.
Depending upon the type of study, required data can be classified into several categories. The broad classifications are described as per the following:
Given the set of data types, it is solely up to the way the researcher wants to present and analyze the data in the study. Falsification and mistakes in identification of data type while data collection may lead to rejection of the entire study.
With a view to helping researchers in the process of data collection, a number of organizations are present with their expertise. “phdbox.in” is one of the pioneers in the field of data collection for dissertation.