Understanding & defining Quantitative Research
Quantitative research is a systematic investigation of collecting quantifiable data through statistical, computational or mathematical techniques. Quantitative research gathers data from the potential and existing customers via sampling methods like surveys, polls, and questionnaires. The result of this research can be depicted in the numerical form. These numbers are necessary for future prediction of a service or a product and make the charges according to the data.
Quantitative research is the experiential study of various observational phenomenons. The main objective of this research is to employ and develop theories, hypotheses, and mathematical models. Moreover, Quantitative research is commonly applied in economics, sociology, health, human development, political science, history and many more. It is also used to verify which of the hypothesis is correct among several.
For example, a survey is conducted to study how much time a doctor takes to attend a patient when he/she walks into the hospital. A template for the survey can be implemented to ask different questions like “how much a doctor takes to see a patient?” or “how many patients are visited by the hospital per day?”
Quantitative research is mostly applied in the social sciences using various statistical systems for the gathering of quantitative data. In this method, statisticians and researchers arrange mathematical theories and frameworks that relate to the number under question.
The templates for Qualitative Research are elaborate, objective, and investigative. The results of this research are unbiased, statistical and logical. Data is collected by employing a structured procedure. Quantitative research is generally conducted on the larger sample that symbolizes the whole population.
Characteristics of Quantitative Research
Some of the most distinguished characteristics of quantitative research are:
- Sample Size: Quantitative data is carried out with a vital size of the sample that symbolizes the targeted market. Appropriate sampling techniques are used to fortify the objective of the research.
- Prior Studies: In this segment, different aspects relevant to the research subject are examined before gathering feedback from the participants.
- Result Generalization: The results of the quantitative method can be generalized among a large number of populations to take the necessary actions for improvement.
- Structured Tools: Structured tools like polls, questionnaires or surveys are utilized to collect quantitative data. The structured tool gathers actionable and in-depth data from the participants of the surveys.
- Close Ended Questions: Close-ended questions are created according to the requirement of the research. These questions collect data and hence are widely implemented in quantitative research.
- Quantitative Data: Generally, quantitative data are represented by the charts, graphs, tables or any other non-numerical forms. This assists in understanding and proving the validity of market research.
Advantages of the Quantitative Research
Some of the major reasons for using quantitative data in the market research are:
- Simple Data Collection: Quantitative research is carried out with a flock of participants who represent the general population. Implementation of a survey or any other method for the quantitative method will conduct and analyze the results that are less time taking.
- Elimination of bias: Quantitative research offers no chance for biasing or personal comments on the results. The outcomes are numerical and are thus fare in maximum cases.
- Collection of accurate and reliable data: As most of the data is gathered, examined and represented in numbers, the conclusions are very much reliable and trustworthy. The number offers an honest outline of the research without any discrepancies and with extreme accuracy.
- A huge scope of Data Analysis: Due to the implementation of statistical methods, quantitative research offers a huge scope of data collection.
Thus we can wrap up this article by saying that quantitative research is used when a researcher wants to test or confirm something. Since it focuses on testing the hypothesis and theories, it is mainly expressed in graphs, tables, and numbers. Quantitative research is utilized to establish a general fact.
Examples of Quantitative Research
Two examples of quantitative research are as the below.
- If any company likes to conduct a CSAT survey, quantitative data is gathered. It can also collect the different metrics based on the goodwill of the enterprise or the brand according to the customer. These metrics can be based on various parameters like pricing, quality, and customer experience. It can be accomplished using NPS or Net Promoter Score, and matrix table questions. These methods offer data in the numeric forms that can be worked upon or studied later.
- An organization that is willing to organize an event can collect feedback from the various attendees about the value of the company. By implementing a survey template for an event, the enterprise can get a clear idea about the customer satisfaction.
Methods for Quantitative Research
Quantitative research is always data-oriented. There are two types of quantitative research methods as below.
Primary Methods for Quantitative Research
Primary methods for quantitative research are the most commonly used method for conducting market research. The main feature of this type of method is that the researcher focuses on gathering the data directly. They do not rely on the data found from the previous research. Primary quantitative research methods can be further classified into three processes which are described as the following.
I) Study Types and Techniques
There are various categories of primary quantitative research. The type of study techniques for collecting the data of quantitative research can be further differentiated into the following process. They are:
A) Survey Research
Survey research is one of the most basic tools for research studies and methodologies. Surveys ask different types of questions to a group of respondents using polls, questionnaires, and web intercept surveys. Each and every organization, being small or big needs to understand what the customers are thinking about their services or products. It also helps them to calculate how all the new features will fare in the market.
By conducting successful survey research, a company can ask multiple queries and gather data from a group of customers. It also assists in analyzing the data that is collected to generate numerical results. This is the first step for collecting data in any type of research.
Moreover, survey research can be conducted among specific or multiple groups of the audience with a comparative analysis. A prerequisite condition for survey research is that the sample collected from the participants must be random. In this way, the researcher can maintain the data accuracy of the obtained results. This is possible as a huge range of respondents can be addressed through random selection.
Traditionally the research was carried out through phone calls or face to face interviews. But today in the world of online media, the survey can be conducted through social media, emails, and chat. There are a total of two kinds of surveys based on the time taken and the type of data requirements. They are discussed in detail below.
1. Cross-sectional Surveys
Cross-sectional surveys are observational in nature. This research is conducted in the circumstances where the researcher collects data from the sample of a targeted population within a given time. In this survey, researchers can examine different variables at a given point in time.
- Data is collected from those participants who contain similar variables except those which are considered for the survey research. This particular variable needs to be constant throughout the research. The characteristics of cross-sectional surveys are:
- This type of survey is mostly applicable in the SME, healthcare industries and retail. Information is gathered without any modification of the parameters in the ecosystem
- More than one variable can be studied, compared and analyzed by implementing this type of research
- The cause-effect relationship between the variables in this type of research cannot be established. This is due to the fact that this research examines variables at a particular time and not across the various time frames.
2. Longitudinal Surveys
Longitudinal surveys are observational in nature that is carried out in different time durations to scrutinize a change in the thought processes and respondent behavior. This time can vary from days to months to even decades. For example, if a researcher is planning to analyze the changes in the purchasing habits of the teenagers for 10 years, then he will have to conduct the longitudinal survey. The characteristics of longitudinal surveys are:
- In this survey, various variables can be compared and analyzed at different time intervals.
- Longitudinal surveys are implied in the situations where a sequence of events is extremely important.
- This type of survey is mostly implied in the applied sciences and medicine. It is also used to observe the changes in the market trends, feedback of the services or products and to analyze client satisfaction.
- Researchers mostly rely on longitudinal surveys to thoroughly inspect the subject before concluding.
B) Correlational Research
Correlational research is a type of investigation that is carried out to create a relationship between the two closely knitted entities. It is also used to observe how one entity can have an impact on another and what are the changes that can be recorded. This research helps to find out the numeric value in the relationships. However, the minimum two groups of participants are necessary to conduct correlational research successfully. Without any assumptions of various aspects, a relationship between the two entities or groups must be found.
Researchers implement this correlational method to correlate multiple variables by employing mathematical analysis methods. Trends, relationships, and patterns between more than two variables are concluded as they remain in their original set up. The impact of one variable upon the other is observed in the process. Researchers also often change the nature of one of the variables to obtain desirable results.
It is also suggested not to draw any conclusions based on correlational research only. This is because the two variables don’t need to be in the sync even if they are interrelated. Some of the most famous examples of correlational research are:
- Relationship between money and fame
- The relationship between the students and its fourth-grade class
- The relationship between depression and stress
C. Causal Comparative Research
Causal comparative research is mainly dependent on the comparison factors. This research is also known as quasi-experimental research. It is mainly implemented by the researchers to conclude the cause-effect equations between more than two variables.
Here one variable is dependent on the other. The independent variable is not manipulated but is established. The impact of the independent variable on the dependent one is observed. These variables should be divided into groups in their natural surroundings.
The conclusions in this research need to be carefully established keeping all the variables in mind of the researcher. This is because all the variables, dependent or independent all exist within the same group. The research is not only limited to the statistical analysis of the two variables. It also extends to the examination of how groups or variables change under the influence of similar factors.
Moreover, the causal comparative research can be applied irrespective of the relation type that exists between the variables. Statistical analysis is utilized to represent the conclusion of the obtained results through this research method. Common examples of causal comparative research are:
- The impact of proper education on the freshman
- The impact of the substantial food provision in the African Villages
- The effect of the drugs on the teenagers
D) Experimental Research
The other name of the experimental research is true experimentation. This research method is completely dependent on one or more theories. The theory has never been planned in the past and is just a belief. In experimental research, an analysis is carried out around disproving or proving a statement.
This research is mainly employed in the social or natural sciences and can include multiple theories. A theory can be defined as a statement that needs to be refuted or verified. After creating the statement, efforts are given to understand whether it is invalid or valid. The characteristics of the experimental research are as follows.
- Schedules for systematic teaching help the children who find it difficult to cope up the present syllabus
- Traditional research systems are more efficient than today’s techniques
- It is a bonus to include responsible nurses for ailing patients
II) Methodologies for Data Collection
The next major step in the primary methods for quantitative research is data collection. This can be classified into sampling methods, surveys, and polls. Let us see these methods in detail.
There are two different types of sampling methods for quantitative research and they are:
1. Probability Sampling
In probability sampling, probability theory is employed to filter the individuals from the population and create the required samples. Participants of the sample are selected through random selection procedures. Each member of the respondents has an equivalent opportunity to be chosen in the sample. There are mainly 4 categories of probability sampling. They are as follows.
- Stratified random sampling: A huge population is classified into various strata in stratified random sampling. Here members are selected randomly. The numerous separate strata should not overlie one another.
- Systematic Sampling: It is a technique where the beginning point of the sample is preferred randomly, while other attributes are selected using a preset gap. This gap is planned by dividing the targeted sample size with the population size.
- Simple random Sampling: It is a simple random selection of the aspects from a given sample. This research method is mainly implied where there are a considerably huge number of populations present.
- Cluster sampling: In this method of quantitative research, the main section is divided into clusters based on the demographic and geographic segmentation parameters.
2. Non-Probability Sampling
In non-probability sampling, the experience and knowledge of the researcher are used to produce the samples. Due to the involvement of the researcher, all the participants of the targeted audience have an opportunity to get selected in the sample. The non-probability sampling is classified into five types and they are:
- Convenience sampling: In this type of sampling, attributes of a sample are chosen based on the proximity of the participants with the researcher. The samples of this technique are easy and simple to implement since there are no parameters involved in it.
- Quota Sampling: Researchers choose elements applying their knowledge of the personalities and targeted traits for the formation of strata. Participants from the different strata are chosen to be an integral part of the sample according to the understanding of the researcher.
- Judgmental Sampling: In judgmental sampling, samples are generated based on the skill and experience of the researcher.
- Consecutive Sampling: It is very much similar to convenience sampling, except the researchers can select a group or a single element of the samples. This method conducts the research consecutively over an important period and then operates the same process with the other samples.
- Snowball Sampling: In snowball sampling, the research is conducted with those target audiences which are hard to get in contact with and extract the information.
Using polls and Surveys
Once the sample is established, then either the polls or surveys can be dispersed to collect the required data for the quantitative research. A survey is a process of collecting data from the pre-defined group of the participants and their insights on the research topic. The total of people a survey can reach is dependent on the time and objective of the research. This makes it one of the most vital elements of carrying out quantitative research.
There are mainly 4 scales of measurement that are fundamental in the creation of MCQ in a survey. The scales are ordinal, nominal, ratio and interval. Without these 4 measurement scales, any MCQ cannot be created. Hence it is absolutely necessary to understand the measurement levels to create a strong survey.
To successfully implement quantitative research, questions that are close-ended in nature need to be used in a survey. They can be MCQs like rating and semantic differential scale questions. Survey design along with the creation is important to conduct primary quantitative research. Proper distribution of the survey is another vital aspect of the survey procedure. There are numerous ways for survey distribution among which the below one is the most popular. They are:
- Buy Participants: The utilization of the sample is the most effective way to conduct quantitative research. Since most of the respondents are experienced and are included in the panel according to their own will, thus responses are much higher.
- Social Distribution: Surveys can be distributed via social media to collect the highest number of answers from those who are responsive to the product or services.
- SMS Survey: A simple and effective way to conduct a survey is through SMS since most people carry a mobile phone with them.
- Email: Sending a survey through email is the most extensively used method for survey distribution. The response rate is also much higher than the other methods.
- Embed the survey in a website: Embedding a survey on the website enables a participant to answer the questions whenever they are in the proximity of the site.
A perfect example of a survey is the CSAT or short survey template for customer satisfaction. CSAT can be quickly created and deployed to gather feedback about what the customer thinks about a brand. It also explains how to reference or satisfy the brand to its clients.
Polls are generated to collect feedback from the close-ended questions of a sample. Polls are mostly commonly implied in exit and election polls. In both of these polls, a large amount of data is gathered using a basic type of question.
III. Techniques for Data Analysis
The third step of the primary quantitative research is data analysis. After raw data collection, it needs to be analyzed properly to conclude statistical presumptions from the research. It is also significant to relate the outcomes to the research objective and establish the relevance of the results.
In data analysis, those aspects need to be included which are not utilized during data collection. The difference between the two required to be noted between what has happened vs what was planned. There are 4 different processes for the statistical analysis and study of quantitative data. The techniques are:
- Conjoint Analysis: In this type of analysis, researchers learn how to make complicated decisions related to purchasing.
- TURF analysis: Totally Unduplicated Reach and Frequency analysis are operated in the circumstances where the source for favorable communication is analyzed. TURF analysis is implemented to understand the potentiality of the market.
- SWOT analysis: Organizations implied this SWOT analysis to evaluate their performance externally and internally. It is also used to create efficient strategies for improvement.
Methods for conducting Secondary Quantitative Research
Secondary or desk quantitative research is a method that collects data from existing or secondary data. Existing data is reviewed and collated to enhance the overall efficiency of the research.
The method involves the collection of existing sources like government resources, research reports, the internet, and libraries. It helps to validate the data that is gathered from the primary quantitative research. Secondary quantitative research also assists in the strengthening and proving or disproving of the collected data. The methods for secondary quantitative research can be classified into 5 categories. They are:
- Non-government and government sources: This type of research can be carried out with the help of non-government and government sources that deal with the report for market research. These are the highest in-depth and reliable data that can be used to prove the validity of quantitative research.
- Educational institutions: Educational foundations research various topics. Hence the reports published by them are a vital source of validation for quantitative research.
- Data in the Internet: With the high application of mobile and internet, it has become easy to conduct quantitative research. Information regarding most current topics is available online, boosting the validity of the data.
- Public Libraries: Public libraries include valid reports of the research that has been conducted on the subject previously. They are a big storehouse of valuable documents and information from which vital data can be collected.
- Commercial sources for Information: Journals, newspapers, radio, TV, and magazines are a large source of collecting information for secondary quantitative data. These types of data have in-depth and first-hand information on the political agenda, market research, demographic segmentation, and economic developments.