Collecting Your Own Data-Primary Research

In every research studies, the scientist wants to identify the truth or they wish to develop meaningful insights into the problem. In order to make any valid conclusion about the research problem or hypothesis, we need valid evidence. Moreover, the evidence can be represented by collecting data (numeric or non-numeric in nature). In any statistical analysis, data collection is the fundamental step and there are two forms of data collection; Primary and Secondary method of data collection. I will describe you the meaning of primary data, examples of primary data collection and different ways of collecting the same.

Primary Data

The researcher collected the Primary data through surveys, experiment, interview, etc, and it is considered to be the best research methodology as the data are collected from the original source. However, before collecting the primary data, the main task of the researcher is to identify the sample population and the mode of data collection.

Examples of Primary Data Collection

• Suppose if you are interested in identifying the sales of a product in the market and make a profitable business plan, then you may conduct a sample survey about the product to selected customers and identify the pattern of sales and fix a target for future years (Niraula, 2019)


• In many psychological experiments, they often collect primary data through lab experiments, questionnaire, etc, to understand the relationship between the variables under study.


• Suppose a research student want to find out which cool drink they like most. Then he/she collect the data by conducting experimental research. That is, he/she take a sample of say 30 people and ask them to choose which drink taste good from the 5 different cool drinks presented before them and recorded the findings for the study.

Primary data can be collected in different ways and are explained as follows:

• Data collection through Interview – In this method, there are two groups: one is the researcher asking questions to the respondents or the interviewer and the other group is the people answering to the questions or interviewee. An interview can be done either telephonic conversation or direct (face-to-face) interview. The benefits of the interview method are that the information is clear and deep, and missing data can be easily identified and we can control the size of the sample. The limitations of this method are it involves longer time to complete, manual mistakes while recording or coding the data and cost incurred is high (Pochiraju & Seshadri, 2019).


• Questionnaires and Surveys – In this case, the researcher frame a set of questions to be asked to the respondents and collect the data by circulating them. Mostly, a pilot study should be conducted when we make use of this data collection method. These data can be collected either offline mode (direct survey like a census) or on-line mode (google forum, email, etc).  The benefits of this data collection are the respondent gets enough time to answer the questions, and the cost of conducting this method is comparatively low. The limitation of this is once the question is framed, we cannot alter in the middle and it requires more time.


• Data collection through observation -This type of data collection is often used in behavioural science. The researcher uses a tool to collect the data. For example, in a teaching requirement process, the person is asked to present a demo to evaluate the capability of the teacher.  The benefits of this method are that it is not related to the past or future outcome and is objective in nature. The limitation is limited information and selected target samples.


• Data through Experiments – This type of data collection is often carried out in the medical field. Suppose a researcher wants to identify the performance of a new drug and he/she conduct an experiment by taking a sample subject. Here the subjects are pre determined because only the patients with certain disease are tested by giving the appropriate drug. The benefits of this method are there is no non-response in the data and it is also objective in nature. The limitation is that human error is possible and expensive.

The main advantages of collecting primary data over the secondary data is that (1) it provides freedom to collect data according to your research objective (2) the recorded data is more accurate than secondary data (3) you don’t need to share the data to others unless if you wish to (4) you can have proper control in the sample size and finally (5) the information is up to date (Gray, 2009).

Statistical support service Once the collected the data then proceed the next phase as statistical analysis. The statistical analysis is used to describe the data structure, classify the data, correlate or identify the relationship, validating the data, predicting the future outcomes in the study. Data analysis service offers the serveral tests that available in the literature for analysing primary data. For example, if the sample size is small, then one may use the t-distribution test and if the sample is large enough then one may use z-test, etc. In addition, there are few situations that the data may be non-numeric in nature, then one can use the classification and clustering technique for analysing the primary data (De Vaus, 1986).

To sum up, primary research involves the proper collection of data and appropriate research objective. The first step of any primary research is to identify the data type and choose the appropriate data collection method and proper statistical tool to make reliable results. The primary data collection method is often accurate and gives real time conclusions. Primary research can be either qualitative or quantitative or a combination of both types in nature. On the basis of the data type you can execute either qualitative or quantitative analysis to make conclusions.

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