Research Writing

# What is quantitative research Characteristics techniques Examples

When the student builds the arguments of his work based on statistical data, he is doing a quantitative research. With this approach, the aim is to generate more accurate and reliable results.

The quantitative approach is a scientific research method that relies on numerical data and statistical analysis, thus focusing on a small number of concepts.

## What is quantitative research?

Quantitative research is, according to Knechtel (2014), a research modality that acts on a problem based on the test of a theory, with variables quantified in numbers. The mode of analysis is statistical, therefore, there is a concern with the quantification of data.

For Knechtel, the quantitative study is concerned with rigorous experimentation, measurement and control of facts.

There are two types of data that can be considered in a quantitative research:

• Primary data: obtained by the researcher, through field research , interacting directly with the original sources.
• Secondary data: surveys carried out by accredited sources, such as the IBGE.

Quantitative research can be used for different purposes. It serves to measure the potential of a market, measure attitudes and behaviors or even identify how many people from a given sample share the same characteristic.

### Characteristics of quantitative research

• Has clarity and objectivity;
• It will always be based on a sample from a population;
• It quantifies the answers to validate (or not) the initial hypotheses;
• It collects concrete and quantifiable data, that is, data that can be transformed into numbers;
• Uses statistical procedures to analyze numerical data;
• Allows classifying variables and establishing relationships between them;
• Can describe the causes of a phenomenon or the relationships between variables;
• Numerical measurements are more important than verbal ones and descriptions.

## Quantitative research techniques

### survey

One of the main ways of collecting quantitative data is survey research . The technique, also called survey research, consists of asking a group of individuals to answer a form with questions

The task of applying a questionnaire became simpler with the creation of the internet. Today, it is possible to create a questionnaire in free software and send the link to respondents through social networks.

Among the digital tools that help in the application of survey research , it is worth mentioning:

Those who are going to collect primary data with a survey need to be concerned with the accuracy of the sample (a significant portion of the investigated population).

Other points that should be checked are the structure of the questionnaire and the budget available to apply the technique.

### Secondary data collection

In this type of investigation, the student accesses a database of a research institute or a company. After collecting the information, he performs a series of quantitative analyses, always following mathematical logic.

### experiments

In several areas of knowledge, it is possible to apply an experiment to obtain quantitative data and analyze them. In this type of technique, it is possible to control some variables and perform manipulations to verify the existence of cause and effect relationships.

## How to do a survey with a quantitative approach?

Below are some tips for doing quantitative research in your work:

### Check the need for a quantitative study

The researcher must analyze his object of study to find out if there is a need to find quantifiable evidence to understand the research problem .

### Choose techniques to apply

Each technique chosen to apply quantitative research should be explained in detail.

Quantitative data can be collected by applying a questionnaire directly to respondents. The method of administration is carried out in person, by explanatory letter, by telephone or via the internet.

The observation of people, events or objects is another resource used in quantitative research. The researcher systematically records this technique.

In general, quantitative data collection respects scales, which are tools filled with numbers and responsible for determining a condition.

The scales are available in other studies in the area, that is, they have already been applied by other authors and validated. In addition, there is the possibility of developing a scale, provided that the aspects to be measured are well delimited and justified by the literature.

### set the sample

Sampling selection cannot be done at random. It needs to be a significant portion of the studied population. Without taking this precaution, the quantitative study loses its credibility and generates unreliable results.

The sample calculation takes into account the size of the population, the margin of error, the degree of confidence and the distribution of the population. The formula is as follows:

Sample size =N Z² p (1-p)(N-1) e² + Z² p (1-p)

Where:

• N
• Z  = the accepted deviation to reach the desired confidence level;
• e  = the maximum margin of error;
• p  = proportion that will be found.

Use an online sample calculator to ease the process of calculating the sample. So, you don’t need to apply this complex mathematical formula.

Example:

A student decided to research the favorite leisure activities of university students. The institution has a total of 5,359 students enrolled. For the confidence index of the survey to be 95%, with a margin of error of 10%, the questionnaire must be applied to a sample of 95 students.

### Analyze the collected data

Quantitative research software itself offers instruments to present the data collected, in the form of graphs or tables. These resources can be exported to Word or PDF, in order to facilitate the organization and presentation of results within the work.

At this stage, it is necessary to describe the data analysis methods and how the information can be compared and transformed into percentages or averages.

The quantitative analysis can be divided into two ways:

• Descriptive statistical analysis: makes descriptions of the quantitative data collected.
• Inferential analysis: the sample data set is expanded to the entire population, that is, generalizations are created.

### Expose the results

The results obtained in a quantitative study cannot be expressed only in numbers. The researcher needs to interpret these numbers and draw conclusions based on his theoretical framework .

### Answer questions in the methodology chapter

• Why did you choose the quantitative approach?
• Who is the population and sample?
• What techniques were used in data collection?
• What scales and questionnaires were used?
• How did you collect the data?
• How did you analyze the data?
• What were the conclusions reached?

## Examples of quantitative research

A Publicity and Propaganda student decided to study the behavior of consumers in a supplement store. For this, he opted for a quantitative research, which used the application of online questionnaires via Google Forms in a sample of customers. The survey was able to:

• Measure the number of consumers who prefer product X;
• Describe the profile of consumers who prefer product X (psychological, socioeconomic and demographic characteristics).
• Measure attitudes, behaviors and purchase intentions.

The questionnaire was applied from June 10 to August 10, 2019, with the participation of 100 respondents. The information collected was transformed into graphs and tables.

When presenting the results in the methodology chapter, the student tried to merge the question in the questionnaire, the graph of the results and the text, analyzing each graphic representation.

## What about qualitative and quantitative research?

To make a survey complete, it is important to combine the quantitative approach with the qualitative one . The first has to do with quantity, while the second is linked to the description of the studied object. When the two methodologies are combined in the study, the qualitative and quantitative research takes shape.

The quali-quanti approach has the role of interpreting numerical and qualitative data, proposing a participatory interaction.

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