What is Quantitative Research?

Quantitative research is the process of gathering as well as analyzing numerical data. Generally, it is used to establish predictions, averages, patterns, and cause-effect relationships between variables under study. Quantitative research is also used to generalize the results of a certain study to the population under consideration. Usually, quantitative market research is used in social and natural sciences.

Quantitative research can also be defined as an organized investigation of occurrences by collecting quantifiable data and carrying out computational, mathematical, or statistical techniques. When carrying our quantitative research, the researcher collects data from potential and existing customers through sampling methods and questionnaires, online polls, online surveys, etc., whose results are depicted in numerical form.

Advantages of Quantitative Research

Often, quantitative research is used to generalize findings and standardize data collection. This approach has the following advantages:

• Replication. It is possible to repeat the study because of standardized data collection procedures and concrete definitions of abstract concepts.
• Direct comparisons of results. A quantitative research study can be reproduced in other social settings, times or with diverse groups of participants. The results obtained can be statistically compared.
• Large samples. Data collected from large samples is analyzed and processed using consistent and reliable procedures using quantitative data analysis.
• Hypothesis testing. Using established and formalized hypothesis testing methods implies that you have cautiously consider and report your research testing methods, data collection, predictions, and variables before drawing conclusions.

Disadvantages (Limitations) of Quantitative Research

Despite quantitative research being beneficial, sometimes it is insufficient in describing complex research topics. It has the following limitations:

• Superficiality. The use of restrictive and precise operational definitions may insufficiently represent complex ideas. For example, the mood concept may be represented through a number in quantitative research, but in qualitative research, it would be explained elaborately.
• Narrow focus. Prearranged measurement procedures and variables can translate to you ignoring other relevant observations.
• Structural bias. Despite the standardized procedures, quantitative research can still be affected by structural biases. Inappropriate sampling methods, imprecise measurements or missing data as some types of biases that can result in the wrong conclusions.
• Lack of context. When executing quantitative research, the researcher often uses unnatural settings such as laboratories or fails to contemplate cultural and historical contexts that can impact data collection and outcomes.

Types of Quantitative Research

There are two ways to conduct quantitative research: primary quantitative research methods and secondary quantitative research methods.

• Primary Quantitative Research

This research method is mostly used to conduct market research. The researcher collects data directly from the sample rather than relying on data previously collected by other researchers.

• Secondary Quantitative Research

This is also known as desk research. In this research procedure, the researcher uses already existing data or secondary data. This available data is then summarized and organized to grow the general effectiveness of the research. Here, data can be collected from libraries, government documents or resources, the internet, and other directed research, etc. secondary quantitative research is normally done to validate data collected through primary quantitative research methods. It is also helpful in strengthening or refuting data collected earlier.one popular procedure of secondary quantitative research is meta-analysis. This is a statistical study that typically combines the outcomes of different other scientific studies. Therefore, it is a summarization of the data that already exists on a certain phenomenon.

Types of Primary Quantitative Research

The following are the four main ways of conducting primary quantitative research.

1. Survey Research

This is the most common and broadly used tool in quantitative research. Surveys are efficient in collecting data by asking appropriate questions to respondents who are assumed to contain relevant information that the researcher is seeking to acquire. In general, a formal questionnaires list is prepared and circulated to the respondents and they report their thoughts. Researchers use a clear approach so that the survey participants are aware of what they are responding to. Generally, respondents are asked about their demographic particulars, and the view that the researcher wants to study. A researcher can conduct a survey through web-intercept surveys, paper-pencil questionnaires, online polls, etc. They are done by both big and small organizations seeking to understand the opinions of their customers regarding their products and services. Surveys are significant as they give organizations a chance to collects data from large populations, ask several survey questions and analyze the numerical outcomes generated from the data collected.

The greatest advantage of surveys is that researchers can select a particular target audience or do the survey across several groups for relative analysis. But, researchers have to randomly sample the respondents to ensure that the research is unbiased and fair and that each respondent, despite their opinions and beliefs, has a fair chance of participating in the survey.

There are two main types of survey research

1. Cross-sectional Surveys

When conducting cross-sectional surveys, the study is done at a single point in time. Thus, cross-sectional surveys do not involve manipulating the study variables, and are limited in this manner. Cross-sectional surveys lets the researcher study various attitudes, characteristics, at the same time. It purposes to give information about a population at that particular moment in time.

1. Longitudinal Surveys

On the other hand, longitudinal surveys involve studying variable over a long period of time and observing emerging changes from time to time. Data is collected from the participants at the start of the study, and then the research collects more data at different time intervals until the study is completed. Longitudinal surveys are most common in medicinal science to evaluate and understand the effects of vaccines, or medicines, in the long-term on participants. Since longitudinal surveys occur over several years, the researcher can determine the series of events that can influence the variables under study.

2. Correlational Research

A correlation is a relationship or an association between two bodies. A correlation research looks at how an entity impacts another and the changes that are observed when one of the entities change. This research method is executed to understand naturally occurring associations between variables. Therefore, you need to have at least two groups to successfully carry out a correlational quantitative research. The researcher is not controlled by the variables in this study, the researcher is just trying to determine whether or not there exists a relationship between two variables. As a correlational study only provides an understanding of the presence of a relationship between two groups, it does not, however, establish causation. Therefore, you should not draw conclusions on the basis of correlational studies; just because two variables are in tune, it does not imply they are interrelated, or that one of them is causing the changes experienced by the other variable.

3. Comparative Studies or Quasi Experimental Research

This is a research method that involves comparisons of groups. It is a research method mostly used when seeking to find a cause-effect relationship between variables. In this case, one variable is dependent on another, typically known as an independent variable. During quasi-experimental studies, you simply establish the independent variable, it is not manipulated or controlled. The researcher is only interested to see its effect on the dependent variable without getting involved. Thus, these groups or variables under study must be developed in a manner that ensures that they occur naturally. Here as well, conclusions drawn from the results of the study should be arrived at carefully since the dependent and the independent variables naturally exist in the groups being studied. The studies are not restricted to the statistical analysis of the variables, but how the variables fluctuate or change under the effect of certain variations.

4. Experimental Research

This is among the most reliant and recommended research methods in social and natural sciences. As indicated by the name, experimental research or experimentation, is normally based on one or more theories as its rationale or driving principle. In this research method, the theory under study has not yet been proven, it is just a speculation. Hence, the purpose of an experiment is to either prove or disprove a theory. If the outcome of the experiment align with the prediction brought forth by the theory, then it is supported. If it does not, the theory is refuted.

Data Collection in Primary Research

After deciding the methodology to use for your primary quantitative research, you can proceed to data collection. Here, collection of data can be divided into sampling methods and data collection using polls and surveys.

Polls and surveys usually involve collecting data from a group of people picked to know their opinions and views. The group of respondents is usually selected or pre-defined before the administration of the survey.

If you intend to use sampling methods as a way of data collection for your primary quantitative research, you should be aware that sampling methods are in two categories: probability and non-probability sampling.

1. Probability Sampling

In probability sampling, participants are selected randomly in a way that gives every participant an equal chance at participating in the study. This sampling method enables researchers to draw strong conclusions about the study and improves its generalizability. Probability sampling is strongly recommended when doing consumer or market research to ensure that the researcher’s bias does not affect his findings. There are four methods of probability sampling:

• Systematic sampling
• Stratified sampling
• Cluster sampling
• Random sampling

Systematic sampling: This is a method where the starting point of a sample is randomly chosen, and all other components are chosen in a fixed interval. The interval is computed by diving the size of the population by the target sample size.

Stratified random sampling: Here, a large population is categorized into groups (strata), and participants in a sample are randomly chosen from the strata. The various isolated strata should ideally not overlay each other.

Cluster sampling: This is a probability sampling technique where the main segment is categorized in clusters, typically using demographic and geographic segmentation parameters.

Simple random sampling: This is just but a random selection of sample elements. This type of sampling technique is executed where there is a considerably large target population.

1. Non-probability Sampling

In non-probability sampling, selection of respondents is non-random in the study. It is a sampling method that is only applicable when the researcher is running on a deadline, or is unable to access particular group members of the general populace. Non-probability sampling methods include:

• Convenience sampling
• Consecutive sampling
• Quota sampling
• Snowball sampling
• Judgmental sampling

Convenience sampling: In this sampling procedure, sample elements are chosen because of one reason only: their nearness to the researcher. The samples are easy and quick to implement because there is no other factor of selection involved.

Consecutive sampling: This is somehow similar to convenience sampling, the difference being that researchers can choose a group of samples or one element and carry out research consecutively over some time and the repeat the process with other samples.

Quota sampling: Through quota sampling, the researcher selects elements using their knowledge of target personalities and traits to form strata. Those in different strata can then be selected to be a part of the sample the way the researcher understands it.

Snowball sampling: This is sampling conducted where the target audience is difficult to contact and obtain information. It is common in situations where the target population is hard to put together.

Judgmental sampling: This is a non-probability sampling technique where samples are generated only based on the skill and experience of the researcher.

Secondary Quantitative Research Methods

The following are secondary quantitative research methods that are popularly used

1. Data accessible on the internet: The high penetration of mobile devices and the internet has made it easy to carry out quantitative research over the internet. You can find information about many research topics online, which aids in boosting the validity of primary quantitative data and proving the significance of previously collected data.
2. Government and private sources: You can also conduct secondary quantitative research using government and private sources dealing with market research reports. The data is in-depth and highly reliable, therefore, it can be used to enhance the authority of quantitative research design.

• Public libraries. Although is now a rarely used method of carrying our quantitative research, the library is still a reliable source of information. Public libraries contain copies of significant research that was done earlier. They are a haven of valuable documents and information where you can easily extract information.

1. Educational institutions: Such institutions do in-depth research on various topics. This makes the reports they publish a significant source of authority in quantitative research.
2. Commercial sources of information: TV stations, radio, magazines, journals, and local newspapers are great sources of secondary quantitative research data. These commercial sources of information have first-hand and in-depth information on demographic segmentation, market research, political agenda, economic developments, and similar subjects.

Characteristics of Quantitative Research Methods

The following are characteristics of quantitative research methods

• Have Measurable Variables

Data collection tools contain items that look for measurable features of the population. The measurable features are known as the variables of the study such as economic status, educational status, the number of children, and age.

• Apply Standardized Research Instruments

These data collection tools include surveys, polls, or questionnaires. Standardized and pre-tested instruments direct data collection hence ensuring validity, reliability and accuracy of data. Pre-testing helps in identification of areas that require revisions in the research instruments. It ensures that the respondents give the expected responses or satisfies the resolve of the researcher to attain the research objectives.

• Assumes an Ordinary Population Distribution

For more dependable analysis of quantitative data, researchers prefer a normal population distribution instead of a non-normal distribution. Naturally, this will require a large population where the numbers depend on the variation of the population’s characteristics. Adherence to the principle of random sampling applies to avoid researcher bias in inferring the outcomes that will defeat the objective of the research.

• Presents Data in Figures, Graphs, or Tables

The data collected through quantitative methods is organized using figures, graphs, or tables to consolidate large amounts of data to demonstrate differences, similarities, or trends among variables. This brings about an understanding to the readers of the research investigation.

• Use Replicable Method

Researchers can replicate the quantitative research method to confirm or verify the outcomes in another setting. This strengthens the authority of groundbreaking findings or groundbreaking thus eliminating the probability of erroneous or false conclusions.

• Predicts Outcomes

Formula derived from data analysis or quantitative models can predict outcomes. You can construct scenarios using complex mathematical computations using computers.

• Application of Measuring Devices

Electronic or advanced digital instruments are used to gather or measure quantitative data. These instruments ensure an accurate and objective collection of data so long as they are calibrated. This means that the instruments conforms to the measurements of a reference instrument, which is considered to be standard.

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