Quantitative research methods of essay writer are used to collect data with numbers rather than words. Quantitative data is collected by human inference and observational study in a controlled environment; the participants are exposed to identical conditions, so that their responses can be compared from one subject to another. The aim of the quantitative research method (QRM) is to use statistical tests and mathematical models in order to give general knowledge on a wide range of social policy issues such as economy, education and health improvement.

This article focuses more on what the QRM definition is. Quantitative research also known as empirical statistics involves collection or measurement of numerical data for analysis which will then lead to conclusions based on the findings.


In most cases, these researches involve using surveys, interviews, field trips, questionnaires and other statistical methods. All these forms of data collection rely on a specific sample population rather than the entire population comprising the social system under study. Quantitative research is based on scientific methodology based on positivism which means that it should not be influenced by any external factors such as emotion or biased views or opinions.

The following are some major stages in quantitative research method:

  1. Subject Selection – Highly trained researchers will select random subjects from the target population in order to ensure that all socio-economic groups are represented and there is equal representation among males and females in a sample size where one third represent male gender while two thirds represent female gender. The chosen subjects should be aged between 18–68 years with a 3 years gap in age variation.

  2. Field Work – The selected subjects will be asked to participate and fill the survey questionnaires with factual information. The required number of questionnaires should fall within any random range as determined by essay writer free research team, assuming that a sample size of 50 is adequate to determine an average cost of living across a country or a region.

  3. Data entry and analysis – All statistical data collected from the surveys should be entered into a computer database and analyzed using statistical software packages which allow for manipulation of data so that information can be presented in tables and charts graphs which can then lead to conclusions reached on issues raised during the research process. This methodology has been successfully used worldwide in all field researches conducted before making decisions with regard to social issues such as education, health and well being of the public.

Another similar definition can be used in this article which states that "Quantitative research refers to the systematic gathering and analysis of numerical data through application of scientific methods like surveys, questionnaires, experiments or observation." Quantitative research is usually conducted with population samples generated from a larger pool of subjects for purposes of generalization. The size of the sample must be sufficient enough to allow an adequate degree of precision in testing the hypothesis raised by the study design. More often than not, quantitative research relies heavily on statistical inference instead of more traditional approaches like case studies or field work whose results can then be replicated across other contexts.

To understand exactly what a quantitative research method is, you need to examine its definition. According to the literature, the quantitative research method is one of the two major ways that a researcher can study and analyze an issue or phenomenon in terms of both its content and its relationship with other related variables.

The most common approach to conducting qualitative research is known as grounded theory methodology by free essay writer team, which was developed by sociologist Max Glaser in the 1960s. Grounded theory relies on coding data through close and repeated readings; reorganizing the data; defining concepts, labels, relationships and dimensions within the data; identifying categories (or themes); testing out emerging codes or categories against new observations; comparing meanings across people; constant comparison during analysis of field notes, documents, pictures etc.; translating into written language for others to understand; and, finally, constant comparison.