Statistical Data Collection Methods - Making Sense of the Mine Field

When use correctly, statistical data can be used to improve an array of areas from efficiency, to lead time, and profit. But in order to make improvements you need to know how the data has been collected initially. This article is about Statistical data collection methods.

There are four main Statistical data collection methods:

Census
Sample survey
Experiment
Observational study

Each of these methods has it's own set of advantages and drawbacks, that's why one must be aware of all their characteristics to be able to choose the right method according to the individual situation. Here is a brief definition of each method:

Census - A census is a case study that acquires data from every population member. For the majority of cases, a census is not practical, due to the large amount of time and cost required to conduct it.
Sample Survey - A sample survey is a case study that obtains data only from a subset of the entire population, not every member, as oppose to Census, so it's much more practical and efficient to carry out, but the results might not be that accurate. For best results using this method it may be appropriate sub-categorize your target group and take a sample set from each sub-category. A basic example would be different ethnic groups.

Experiment - The experiment is a controlled study in which researchers try to understand the cause-and-effect relationships, how one thing affects another.

Observational study - Observational studies also try to discover the cause and effect relations, but unlike experiments, they are not able to control how subjects are assigned to groups.

As it was already pointed out, every method has its own pros and cons, so one must be able to know and make a decision regarding which method should be applied in a given situation. There are three factors that should affect this decision and they are - resources, generalizability, causal inference.

If resources are the main factor, then obviously with such a large population, a sample survey has an advantage over census. If the sample survey is well designed, then it can definitely provide results that are really close to the actual figures (high level of accuracy), and it will be done in a quicker and cheaper manner, requiring less man power than a census.

Generalizability stands for applying findings from a sample study to a larger population. Generalizability requires random selection. In case the participants in a study are randomly selected from a larger population, it is appropriate to generalize study results to the larger population, otherwise it might provide accurate results.

Statistical data collection methods are essential for sustainable economics, social and environmental development. We are living in the 'Information Age' where certain data sets are growing in size and complexity, reaching massive proportions, that's why such data collection methods are so important.

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Various Methods of Data Collection

Professionals in all the business industries widely use research, whether it is education, medical, or manufacturing, etc. In order to perform a thorough research, you need to follow few suitable steps regarding data collection. Data collection services play an important role in performing research. Here data is gathered with appropriate medium.

Types of Data

Research could be divided in two basic techniques of collecting data, namely: Qualitative collection of data and quantitative collection. Qualitative data is descriptive in nature and it does not include statistics or numbers. Quantitative data is numerical and includes a lot of figures and numbers. They are classified depending on the methods of its collection and its characteristics. Data collected primarily by the researcher without depending on pre-researched data is called primary data. Interviews as well as questionnaires are generally found primary data/information collection techniques. Data collected from other means, other than by the researcher is secondary data. Company surveys and government census are examples of secondary collection of information.

Let us understand in detail the methods of qualitative data collection techniques in research.

Internet Data: Here there is a huge collection of data where one gets a huge amount of information for research. Researchers remember that they depend on reliable sources on the web for precise information.
Books and Guides: This traditional technique is authentically used in today's research.

Observational data: Data is gathered using observational skills. Here the data is collected by visiting the place and noting down details of all that the researcher observes which is needed for essential for his research.

Personal Interviews: Increases authenticity of data as it helps to collect first hand information. It does not serve fruitful when a big number of people are to be interviewed.

Questionnaires: Serves best when questioning a particular class. A questionnaire is prepared by the researcher as per the need of data-collection and forwarded to responders.

Group Discussions: A technique of collecting data where the researcher notes down details of what people in a group has to think. He comes to a conclusion depending on the group discussion that involves debate on topics of research.

Use of experiments: To obtain the complete understanding researchers conduct real experiments in the field used mainly in manufacturing and science. It is used to obtain an in-depth understanding of the researching subject.

Data collection services use many techniques including the above mentioned for collection. These techniques are helpful to the researcher in drawing conceptual and statistical conclusions. In order to obtain precise data researchers combine two or more of the data collection techniques.


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