Tuesday, September 22

8 Useful Quantiative Data Collection Methods and Techniques

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Quantitative data collection methods are aimed at testing hypothesis derived from theory and/or to estimate the size of a phenomenon of interest. Quantitative data is used to challenge a viewpoint derived from theory and to determine the potential scope of a particular area of interest.

While quantitative data collection techniques used for research involve the numeric collection, quantitative data collection allows market researchers, through the use of numbers, to evaluate results using statistical analysis. The best quantitative data collection methods include:

1. Quantitative Surveys

Quantitative surveys have close-ended questions with answer choices provided as options for the respondent. The respondent does not have to come up with a self-created answer but is required to select from the choices offered.

The advantage of a quantitative survey is that it enables researchers to make generalized decisions out of data. This is because the questions are standardized. Besides, quantitative surveys are ideal for surveying large numbers. However, they limit the respondents’ responses to just the provided answer options.

2. Interviews

We use interviews to gather quantitative data by asking standardized questions. They include face-to-face interviews, telephone interviews, and computer-assisted interviews. Face-to-face interviews allow the researcher to get clarifications on interviewee responses. However, on the flip side, it can be quite challenging when dealing with large sample size or group of interviewees. It is also an expensive method in terms of the money and time it takes.

Computer-assisted interviews are a variation of face-to-face interviews, but the data obtained from the interviewee is entered directly into a database through a computer.

Telephone and online interviews have the advantage of savings on transportation cost, allowing more extensive coverage. However, the data quality derived as a result may be questionable, especially in terms of impartiality.

3.  Quantitative Observation

Data is collected by the use of the quantitative observation method through systematic observation, for instance, by counting the number of users present in a given area of interest or using a specific service.

These quantitative data collection methods involve natural observation using senses. The aim is to answer the question ‘what’ rather than ‘why’ or ‘how.’ However, these quantitative data collection methods have one serious shortcoming: senses are not infallible. A researcher may not have a good grasp of his or her feelings, and their perception of situations and people could be prejudiced.

4. Experiments

Researchers often make use of experiments to gather data. The various types of investigations include; laboratory experiments, field experiments, and natural experiments. Quantitative methods of investigations seek to manipulate an independent variable and at the same time maintain varying degrees of control over other variables (most likely the dependent variables).

In laboratory experiments, the researcher conducts the experiment in a standard scientific setup, using a controlled environment. In field experiments, the researcher may not have full control of variables, but they can still manipulate them. Natural experiments involve letting the independent variable to naturally occur as the researcher observes the effects of this natural process.

5. Questionnaires

There are two types of questionnaires used for research purposes; mail and web-based questionnaires. Questionnaires often make use of checklist and rating scales. These two devices in a survey are used to quantify people’s behaviour and attitudes. Mail questionnaires have the advantage of saving the researchers time and money. It is more efficient since it can be sent to a large number of people.

Web-based surveys, on the other end, involves sending e-mails to selected respondents, who on accessing the e-mail, are taken to a secure address where they complete the questionnaire. This type of questionnaire is highly cost-effective, quicker, and less detailed.

6. Rating Scales

This quantitative method of data collection is especially useful in scenarios where the researcher seeks to establish the respondent’s satisfaction with a service. It is essential for the rating scales to include questions that are easily understood by respondents.

Every scale point ought to be easy for respondents to interpret and should accommodate different viewpoints.

7. Census

A census has the most significant varying scale imaginable. It is arguably the most comprehensive, systematic way of acquiring and recording information on a target demographic.

Smaller scale censuses can be conducted in a range of formats that are accessible to all disciplines/fields, ranging from local governance to charity organizations, and teacher to international governance.

8. Probability Sampling

Probability sampling is a form of random selection that allows the researcher to make probability statements using sample data gathered randomly from a target demographic. There are three types of probability sampling: simple random sampling, systematic random sampling, and stratified random sampling. Probability sampling helps researchers obtain sample representative data of the target audience.

Quantitative data collection methods, unlike qualitative ones, usually make use of larger samples. This is because their measurable nature makes this possible and more natural. Data collected through quantitative methods can be readily quantified and generated into numeric form, which is then mathematically converted and processed into useful information.

This method of data collection is measurable in nature, larger sample sizes are used. Numeric outcomes can be used strategically. They are credible and useful in decision making. However, the disadvantage of data gathered through quantitative methods is that it may not capture explanatory information.


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Fiona Thompson

Staff writer / Avid internet junkie / Devoted music aficionado

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