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What is quantitative research?
Quantitative research is defined as a systematic investigation of phenomena by gathering quantifiable data and performing statistical, mathematical, or computational techniques. Quantitative research collects information from existing and potential customers using sampling methods and sending out online surveys, online polls, questionnaires, etc., the results of which can be depicted in the form of numerical. After careful understanding of these numbers to predict the future of a product or service and make changes accordingly.
» An example of quantitative research is the survey conducted to understand the amount of time a doctor takes to tend to a patient when the patient walks into the hospital. A patient satisfaction survey template can be administered to ask questions like how much time did a doctor takes to see a patient, how often does a patient walks into a hospital, and other such questions.
It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations
A. Techniques and Types of Studies
There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are:
By conducting survey research, an organization can ask multiple survey questions, collect data from a pool of customers, and analyze this collected data to produce numerical results. It is the first step towards collecting data for any research.
This type of research can be conducted with a specific target audience group and also can be conducted across multiple groups along with comparative analysis. A prerequisite for this type of research is that the sample of respondents must have randomly selected members. This way, a researcher can easily maintain the accuracy of the obtained results as a huge variety of respondents will be addressed using random selection. Traditionally, survey research was conducted face-to-face or via phone calls but with the progress made by online mediums such as email or social media, survey research has spread to online mediums as well.
Traditionally, survey research was conducted face-to-face or via phone calls but with the progress made by online mediums such as email or social media, survey research has spread to online mediums as well.
There are two types of surveys, either of which can be chosen based on the time in-hand and the kind of data required:
In cross-sectional surveys, the same variables were evaluated at a given point in time, and in longitudinal surveys, different variables can be analyzed at different intervals of time.
Longitudinal surveys are extensively used in the field of medicine and applied sciences. Apart from these two fields, they are also used to observe a change in the market trend, analyze customer satisfaction, or gain feedback on products/services.
In situations where the sequence of events is highly essential, longitudinal surveys are used.
Researchers say that when there are research subjects that need to be thoroughly inspected before concluding, they rely on longitudinal surveys.
Researchers use this quantitative research design to correlate two or more variables using mathematical analysis methods. Patterns, relationships, and trends between variables are concluded as they exist in their original set up. The impact of one of these variables on the other is observed along with how it changes the relationship between the two variables. Researchers tend to manipulate one of the variables to attain the desired results.
Ideally, it is advised not to make conclusions merely based on correlational research. This is because it is not mandatory that if two variables are in sync that they are interrelated.
» Example of Correlational Research Questions:
The relationship between stress and depression.
The equation between fame and money.
The relation between activities in a third-grade class and its students.
This research method mainly depends on the factor of comparison. Also called quasi-experimental research, this quantitative research method is used by researchers to conclude the cause-effect equation between two or more variables, where one variable is dependent on the other independent variable. The independent variable is established but not manipulated, and its impact on the dependent variable is observed. These variables or groups must be formed as they exist in the natural set up. As the dependent and independent variables will always exist in a group, it is advised that the conclusions are carefully established by keeping all the factors in mind.
Causal-comparative research is not restricted to the statistical analysis of two variables but extends to analyzing how various variables or groups change under the influence of the same changes. This research is conducted irrespective of the type of relationship that exists between two or more variables. Statistical analysis is used to distinctly present the outcome obtained using this quantitative research method.
Example of Causal-Comparative Research Questions:
The impact of drugs on a teenager.
The effect of a good education on a freshman.
The effect of substantial food provision in the villages of Africa.
There can be multiple theories in experimental research. A theory is a statement that can be verified or refuted.
After establishing the statement, efforts are made to understand whether it is valid or invalid. This type of quantitative research method is mainly used in natural or social sciences as there are various statements which need to be proved right or wrong.
Traditional research methods are more effective than modern techniques.
Systematic teaching schedules help children who find it hard to cope up with the course.
It is a boon to have responsible nursing staff for ailing parents.
Gather research insights
B. Data collection methodologies
The second major step in primary quantitative research is data collection. Data collection can be divided into sampling methods and data collection with the use of surveys and polls.
Data collection methodologies: Sampling methods
There are two main sampling methods for quantitative research: Probability and Non-probability sampling.
Probability sampling: A theory of probability is used to filter individuals from a population and create samples in probability sampling. Participants of a sample are chosen random selection processes. Each member of the target audience has an equal opportunity to be selected in the sample.
There are four main types of probability sampling:
Simple random sampling: As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.
Stratified random sampling: In the stratified random sampling method, a large population is divided into groups (strata), and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another.
Cluster sampling: Cluster sampling is a probability sampling method using which the main segment is divided into clusters, usually using geographic and demographic segmentation parameters.
Systematic sampling: Systematic sampling is a technique where the starting point of the sample is chosen randomly, and all the other elements are chosen using a fixed interval. This interval is calculated by dividing the population size by the target sample size.
Non-probability sampling: Non-probability sampling is where the researcher’s knowledge and experience are used to create samples. Because of the involvement of the researcher, not all the members of a target population have an equal probability of being selected to be a part of a sample.
There are five non-probability sampling models:
Once the sample is determined, then either surveys or polls can be distributed to collect the data for quantitative research.
Using surveys for primary quantitative research
A Survey is defined as a research method used for collecting data from a pre-defined group of respondents to gain information and insights on various topics of interest. The ease of survey distribution and the wide number of people can be reached depending on the research time and research objective make it one of the most important aspects of conducting quantitative outcome research.
Fundamental levels of measurement – nominal, ordinal, interval and ratio scales
There are four measurement scales that are fundamental to creating a multiple-choice question in a survey. They are nominal, ordinal, interval, and ratio measurement scales without the fundamentals of which, no multiple-choice questions can be created. Hence, it is crucial to understand these levels of measurement to be able to develop a robust survey.
Use of different question types
To conduct quantitative research, close-ended questions have to be used in a survey. They can be a mix of multiple question types including multiple-choice questions like semantic differential scale questions, rating scale questions, etc.
Survey Distribution and Survey Data Collection
In the above, we have seen the process of building a survey along with the survey design to conduct primary quantitative research. Survey distribution to collect data is the other important aspect of the survey process. There are different ways of survey distribution. Some of the most commonly used methods are:
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