Reducing the contribution of bias through conducting a Quantitative Research!
Quantitative research is a structured way of gathering and analyzing data obtained from different sources. Computational, statistical, and mathematical tools are used in this kind of research to acquire results. The purpose of the quantitative research is to quantify the problems and understand how prevalent they are by looking for generalizable results to a larger population [1].
Types of quantitative research designs:
There are four main types of quantitative research designs as listed below:
Generally, the differences between these four types primarily depend on the degree the researcher designs for control of the variables in the experiment.
Data Collection Methods:
There are many different types of data collection methods that can be used in quantitative research. Typical quantitative data gathering strategies include: applying surveys with closed‐ended questions (e.g., face-to-face and telephone interviews, mail questionnaires, etc.); observing and recording well‐defined events (e.g., counting the number of patients waiting in emergency at specified times of the day); and obtaining relevant data from management information systems [4].
The next step to be taken after data collection is analyzing the collected data. Independent sample t-tests, correlated t-tests, variance calculations, and regression analysis are some examples of analytical tools which are used to analyze the collected data.
Overall, quantitative research deals with numerical data and statistics. Because of being simple and straightforward, it is preferable among many groups of people. How many and How much types of questions are the questions which are answered in this kind of study. Considering these characteristics, like other kinds of research, this type of study has its own pros and cons. One of the outstanding advantages of quantitative research is that it is very objective, and the bias of the researcher has no contribution in the study and he or she just measures the amount of the occurrence of variables. Besides, this advantage, a prominent weak point of this type of research is that it cannot provide a deep understanding of the analyzed items because, in this kind of research, the context of the study or experiment is ignored.