Quantitative descriptive research: definition, types,methodology,methods,characteristics,examples and advantages

How do we define the term quantitative descriptive research? Is it the same as quantitative correlational research or quantitative causal-comparative? Look at this… 


1.1 Definition

Quantitative Descriptive Research is a Non-Experimental type of research whereby the variables are measured using numerical terms although the variables under interrogation are not manipulated by the researcher. This type of research is commonly known as Descriptive Research as stated in our article on descriptive research which classifies types of research on the basis of “purpose of research”. In our current discussion, we are adding the word “quantitative” so as to emphasize that the variables are measured using numerical terms.  Quantitative descriptive research uses two methodologies/designs, namely; observational research and survey research methodologies.


NOTE1: Observational Research

Observational research is quantitative descriptive research where by data collection is done through observation. The design requires that the researcher collect data by devising a method where by although the process of data collection is through observation, the information is translated in to numeric form such as frequency, percentage, tally numbers etc. So, the key point here is that the researcher has to quantify character which have been observed. For example, if the researcher wants to measure corruption in a country. Then, he/she can design a method of using tally numbers such that anytime there is a case of corruption, then this is recorded in a tally sheet. Further, for the researcher to know how a country is corrupt, he/she will then compare the tally numbers in a certain period with the set benchmark tally score which has already been predetermined or given.

NOTE2: Survey Research

Survey research is another type of quantitative descriptive research which advocates use of surveys or questionnaires to collect data pertaining the behavior of subject matter. It entails distributing of surveys or questionnaires to a big sample or the whole population if it is manageable so as to collect data. Since the purpose of this survey research is to describe physical characteristics of a population, it is much in order that the sample be selected using a probability sampling technique to ensure more accurate representation of the sample to the population.


Types of survey research

Survey research can be classified in to three aspects based on the manner in which the researcher is formulating the research problem. These categories are; descriptive, cross-sectional, and longitudinal.

1.Descriptive Survey Research

It is a research design which is set to collect data for the simple purpose of describing the character of the subject matter. It is a one point in time approach of collecting data. For instance, if the researcher wants to study on the level of concentration of members in the church, he/she will randomly distribute the survey instruments to the selected sample and have them fill them and return as supposedly.


2.Cross-sectional Survey Research

It is a research design/study which involves investigation of features of different samples or populations where by the are taken at one point in time. For instance, the researcher may wish to carry out a measurement on cross-sectional study about the study habits of grade six pupils in two, three or four different schools in a certain location. All the pupils making up the sample would be surveyed at the same point in time. Where the cross-sectional survey is conducted for the whole population, it is referred to as a census.


3.Longitudinal Survey Research

It is a research design/study which involves the investigation of the characteristics of respondents where by the measurements are taken at different point in time. For instance, the researcher may wish to carry out longitudinal study on the study habits of grade six pupils in certain school in a particular location. All the pupils making up the sample would be surveyed at different point in time. In other words, the same group of participants is studied over an extended period of time, which naturally involves the administration of several surveys at particular time intervals such as after one year, after another one year and after another one year and so on and so on.

Longitudinal survey research is further categorized into;

Trend study is a longitudinal survey study that scrutinizes changes within a specifically identified population over time with an aim of learning the trend thereof for decision or planning purposes.

Cohort study is longitudinal research which investigates characteristics of a certain group which is a sub-group of another group which was being studied in the previous time. The sub-group is commonly referred to as “cohort”. The kind of longitudinal research happens when the initial group identified was being investigated over a certain characteristic and then further, another sub-group is picked from the previous main group to be investigated over another characteristic. The sub-group should be having the characteristics of the main group for it is a member. For example, a longitudinal study may focus on studying the sleeping habits of children who are under five years in certain families. If the researcher establishes that the children selected have that particular sleeping habit, another group out of this group (i.e., sub-group) is selected to find out if they know how to communicate fluently in their mother tongue. The sub-group being tested of their fluence in mother tongue is a cohort. Hence the study is cohort research.



Panel Research is a study which investigates a characteristic in the same group same sample over a long period. In a panel study, the researcher examines the exact same respondents over a specified time frame. For example, the researcher would select and survey a group of children in year 2018 survey the same children in 2020, and once again repeat the same interrogation for the same children in 2022. So, longitudinal study of panel type deals with the same sample, population or group over a long period set.

Quantitative descriptive research methodology

2.1 Definition

Quantitative Descriptive Research Methodology is the rational process or step by step blueprint on how to solve a research problem that entails a variable which can be measured numerically in terms of 0, 0.5, 1, 2, 3.3, 4…. nth digit etc. Quantitative Descriptive Research methodology involves selecting a logical process on the topic to be studied. That is the study or research problem, how specific objectives of the study will be recognized/or framed. Identification of research gaps to be filled, the methods used in documentation of the study population and sample size determination, type of data to be collected and how it will be collected and analyzed, data presentation and clarifications thereof and the broadcasting of the investigation outcome.


Quantitative Descriptive Research methodology is the intellectual aspect behind the methods we use in the context of our research study. This provides a groundwork as to why one is using a particular method or procedure at a specific phase in the research progression and not others so that research outcome is accomplished either by the researcher or another scholar.

2.2 Quantitative Descriptive Questions Research Methodology tries to Answer


Quantitative research aims at answering one aspect of a question. That is;

What kind of questions only!


The following matrix portrays the link between quantitative descriptive type of research and the type of research methodology adopted and then an explanation of the logical approach associated with this category and then in the last column, the research method(s) used in formulating the research problem. Remember these methods are specifically for quantitative descriptive research which is a sub-set of Quantitative research.

2.3 Quantitative Descriptive Research Methodology-Diagrammatic Approach

The following diagram represents a summary of logical roadmap to be adhered to in descriptive research methodology where Quantitative or Numerical methods are used to measure/gauge the study variables. This case is more biased on survey descriptive research.


2.4 Logical Steps; Quantitative Descriptive Research Methodology

The following logical steps describe the Quantitative Descriptive Research methodology. From step one to nine, it represents a logical way of how systematically the subject matter need to be dealt with. Remember that in this approach, the researcher is only curious of establishing how things work.


2.4.1 Step 1; Topic Identification

This is the first step in Quantitative Descriptive research where by the researcher has to come up with the area of study based on the area of interest. Under step one, the researcher will embrace thematic topic by posing him/herself descriptive affiliated research questions such as “what is the purchases cost level of product M in the regional market?”  OR


 “What is the purchasing pattern of a certain magazine amongst the married people in Kingstone in Jamaica?”


2.4.2 Step 2: Literature Review

In this step, the researcher, interrogates past studies relevant to the area of interest or topic of study. The aim being to highlight the conceptual, methodological and contextual research gaps to help in development of the appropriate survey, interview inquiries/questions and framing of data collection procedures as well.


2.4.3 Step 3: Identification & Selection of Research Participants

Since the main aim of Quantitative descriptive research is to generalize the end results on the population, there is need at this stage to identify the target population. Out of this population, a sample is drawn using a probabilistic sampling technique so as to give each individual equal opportunity to participate in the study.


2.4.4 Step 4: Identification of Appropriate Data Collection Tool

This step involves identification of the most appropriate data collection tool by the researcher. Quantitative descriptive research has a wide spectrum of such tools such as direct administration of a survey, a mail survey, a telephone survey, interviews, e-mail surveys, and web-based surveys. The most suitable approach depends on circumstances prevailing which may favor one method as compared to another.



The researcher chooses the most suitable tool to collect data. Based on the nature or the circumstances the participants are in, the researcher can rely on either face-to-face survey, E-mail survey, a telephone call or survey, or interviews, to mention but a few.


2.4.5 Step 5: Undertake Ethical Precautions

After pre-determining the participants in the study and selecting the approach to use when collecting data, the next step is to disseminate survey to the sample selected, this is achieved by seeking permission from the right authority. So, the researcher prepares a cover or introductory letter to go together with the surveys. Basically, the content of the letter entails the message of assurance of privacy and confidentiality protection strategies for the respondents and also the benefits thereof.


2.4.6 Step 6: Test of Data Collection Tool

After choosing the right data collection tool, the next step is to assess the appropriateness of the tool. This can be achieved through many ways one of them being the pilot test. Pilot testing is a key process in data collection mission for the researcher has to ensure that the data collection tool is effective in capturing the information that is required for data analysis. The purpose of pilot testing of the data collection instrument/tool is to find out if the level of understandability of the respondents are as per the expectations. This approach avoids cases where by the questions in the tool are vague and not clear. It can be frustrating if the participants captured to play a role in the research assignment do not understand the questions or they may do wrong interpretation.



Therefore, a pilot test should be undertaken before actual data collection is carried out. This exercise entails randomly selecting a smaller sample from the main sample and go forth to collect data from respondents using the same data collection tool to test the waters. This process gives the researcher a hint on how effective the tool is and whether there is need to revise the tool before actual data collection. Classical authors such as Kothari (2009) and Sekaran (2006) recommend a 1% sample size for a pilot study and Mugenda and Mugenda (2009) too, states that the size of a sample for the purpose of piloting should be between 1% and 10% of the sample size. It is advisable to exclude the portion of sample used for piloting from main data collection exercise.


2.4.7 Step 7: Data Collection

As usual, in this step, the actual data is collected using the appropriate data collection tool. In this case, a survey tool is suitable if the data collected is quantitative descriptive in nature.


2.4.8 Step 8: Data Analysis


Data analysis for survey cases apply statistical/numerical procedures where hard statistics such as frequency distribution, descriptive statistics such as sample mean, sample standard deviation, sample variance, correlation coefficients and group comparisons are relevant.


2.4.9 Step 9: Research Findings

Research findings stage is the last step and the end to the means in research exercise. The step involves provision of solutions to the research question(s) the investigator had from the beginning. On getting the answers to the research questions, then the researcher can make inferences about the population.in other words, he/she can generalize.


Quantitative descriptive research methods

Does quantitative descriptive research methods for formulating a research problem the same as quantitative descriptive research method for data analysis? The answer is NO. Look at the definitional differences as per our explanation below

3.1 Definition

Research methods are all the techniques that are utilized in all the stages of research processes. They are tools used to ensure the end results of research task are accomplished. These techniques vary from one stage of research process to another. These methods are further classified in to two categories, namely;

a) Pre-Data analysis methods

b) Data Analysis related methods

Quantitative descriptive research uses survey, systematic observation and secondary research methods for the purposes of formulating the research problem which are some of the methods which fall under pre-data analysis category.  However, in this discussion of Quantitative descriptive research, we will focus on main methods of data collection which are also pre-data analysis in nature. That is; observation and survey methods.

Observation data collection method

As discussed earlier, this method involves collecting of data by doing observation of the respondent’s character in the natural/physical settings. The data should be recorded in numeric terms or mode.



Survey Data Collection Method

This method of data collection involves use of questionnaires and other different types of surveys to capture the respondent’s characteristics. Those types of surveys are, namely; direct administration of surveys, mail surveys, telephone surveys, interviews, e-mail surveys, and web-based surveys. 


Direct Administration Survey

Direct administration survey is a method of data collection applicable when the whole population is reachable. All the members of the targeted population are available and it is possible to collect data at 100% assurance level.  The researcher disseminates the survey instrument on his own without a research assistant. This approach translates in to a very high survey return rate which assures the researcher valid results.  This approach works well when the researcher is in proximity to the location where the respondents are.


Mail surveys data collection method


As the name suggests, mail survey data collection method is an approach of distributing surveys to the potential respondents by using mails. It involves administering the survey instrument to the population or the sample identified whereby a hard copy is issued and   the researcher expects the survey to be filled and returned as soon as stated in the instructions given. Mail survey method enables the researcher to cover a wider coverage of the respondents although it is a little bit expensive. 



Telephone surveys data collection method

As the name suggests, the method uses telephone gargets to communicate with the respondents. This has proven to be costly. The method entails making calls either using land line telephones or cell phones to communicate. This survey method requires both parties to be having a phone handset and the surveyor has to recite all the questions to avoid making mistakes when interrogating the respondent.  


Interview survey data collection method

Interview data collection method involves collection of data face to face whereby the researcher has to aval him/herself to the physical locale of the respondent.  Interviews are costly for the researcher has to travel to and from and again if research assistants are used, then they have to be trained on the interview protocols to avoid ineffective responses from the participants.


E-Mail survey data collection method

As the name suggests, the method uses E-Mail accounts to communicate with the respondents. This has proven to be cheap. The method entails sending surveys to individual respondents using their e-mail accounts. This survey method requires both parties to be having an e-mail account that is active. The prepared survey is attached to the email platform and sent to the respondent who is expected to respond within a specific period.



Web-based survey data collection method

As the name suggests, the method uses website platform to communicate with the respondents. This is also cheap. The method entails sending surveys to individual respondents using their e-mail accounts via the sender’s website. This survey method requires the respondent to have a way of accessing information in the website. The prepared survey is attached to the website platform and sent to the respondent who is expected to respond within a specific period.

Characteristics of quantitative descriptive research

  1. Measurement of variables which represent the characteristics of the subject matter is in numeric form.
  2. Data collection is either through observation or surveys.
  3. The data is collected from the subject matter which is in its natural or physical phenomenon.
  4. There is no manipulation of the variables for this type of research is non-experimental in nature.
  5. Data is collected either at one data point or several data points.
  6. It is descriptive in nature-this research only aims at describing or giving a narration of the character of the subject matter and does not show any relationship or causality.
  7. Foundational-this research is the basis of other highly ranked research for it lays the basis of the nature of the variables that exists. Hence giving a hint of whether they correlate or cause other variables to change. This then becomes the basis for further research.
  8. Generalizability-research findings are always generalized. That is, the research findings gotten from the sample is used to generalize about the characteristics of the whole population. 

Advantages of quantitative descriptive research

  1. Objectivity-the researcher just observes the characteristics of the subject matter or unit of observation with his/her hands off from any manipulation. Hence no researcher biased influence.
  2. Time saving- this type of research is time saving especially when the method of observation is used.
  3. Increased response rate-the data collection that involves use of direct administration of survey instruments tend to have almost 100% survey response. Even when questionnaires are issued in this manner, the questionnaire response rate is very high.
  4. Wide coverage of data collection-the survey method of data collection especially when website and e-mail mode of distribution is used reaches far and wide places. This assures the researcher of sample size which is a true representation of the population under study.
  5. Cost effective-when collecting data using web-based survey and e-mail approach, fewer financial resources are utilized. Hence the research design is cheap.
  6. Efficient population representation-the sample size used in survey is always large enough to represent the whole population. This assures the researcher of valid data for conclusive research findings.
  7. Generalization- this type of research allows for generalization of research findings from the sample and therefore it is not a must to use the whole population which may be costly and time consuming.
  8. Customization-under quantitative descriptive research, there are various/wide optional methods of data collection such as one data point collection approach, many data point data collection, panel research design, cohort and so on and so on. These approaches make it possible to meet the needs of many stakeholders.

Disadvantages of quantitative descriptive research

  1. Lack applicability in some circumstances-methods of reaching the respondents such as use of e-mails require both parties, that is the researcher and the respondents to have a cell phone or a computer. This is not the case especially in the rural areas for the developing economies.
  2. Outdated data-where data collection involves many data points in time, the old data collected may turn to be irrelevant in decision making. For example, if the researcher was collecting data on consumer behavior of customers loyal to product EXE of X company limited for the next ten (10) years. You see, by the time ten years will be over, the product version or customer taste will have changed to other more appealing products. So, the initial data pertaining product EXE will be useless.
  3. Does not show causality effects between or amongst variables. As the name suggests, quantitative descriptive research does not show cause-effect relationships between variables.
  4. Bias personal opinion-responses gotten from the survey study have high chances of being wrong. This is because the respondents may answer questions in a manner to please the researcher or the research assistant. This makes the data unreliable.

About the Author - Dr Geoffrey Mbuva(PhD-Finance) is a lecturer of Finance and Accountancy at Kenyatta University, Kenya. He is an enthusiast of teaching and making accounting & research tutorials for his readers.