What are quantitative research sampling methods?

By Riya Jain & Priya Chetty on February 17, 2020

The quantitative research sampling method is the process of selecting representable units from a large population. Quantitative research refers to the analysis wherein mathematical, statistical, or computational method is used for studying the measurable or quantifiable dataset. The core purpose of quantitative research is the generalization of a phenomenon or an opinion. This involves collecting and gathering information from a small group out of a population or universe.


To find out what drives Amazon’s popularity as the most preferred e-commerce company, a small group of Amazon’s customers can be surveyed. It will help arrive at a consensus on the most significant traits that make it successful.

Therefore, an assumption about a population is based on a small or selected dataset. In order to derive accurate results, it is essential to use an appropriate sampling method. The purpose of this article is to review different quantitative sampling methods and their applicability in different types of research.

Quantitative research sampling methods

By examining the nature of the small group, the researcher can deduce the behaviour of the larger population. Quantitative research sampling methods are broadly divided into two categories i.e.

  1. Probability sampling
  2. Non-probability sampling
Quantitative research sampling methods
Figure 1: Quantitative research sampling methods

Probability sampling method

In probability sampling, each unit in the population has an equal chance of being selected for the sample. The purpose is to identify those sample sets which majorly represent the characteristics of the population. Herein, all the characteristics of the population are required to be known. This is done through a process known as ‘listing’. This process of listing is called the sampling frame. As probability sampling is a type of random sampling, the generalization is more accurate.

Probability sampling is quite time-consuming and expensive. Hence, this method is only suitable in cases wherein the population are similar in characteristics, and the researcher has time, money, and access to the whole population. Probability sampling is further categorized into 4 types: simple random, systematic, stratified and cluster sampling. The figure below depicts the types of probability sampling.

Figure 1: Types of probability sampling

The difference between and applicability of these sampling methods are depicted in the table below.

Qualitative Research Sampling Method Sampling TypeMeaningApplicableExample
Probability Sampling MethodSimple RandomRandom selection of the units from a population.Suitable for a small population. Expensive and time-consuming. Requires a sampling frame. Variability in the characteristics is not significant. A survey is conducted in a company of 100 employees for determining their satisfaction level. 20 of them are selected at random.
SystematicSelection of units from a population at regular intervals. Suitable for a small population.
Applicable when the researcher has time and money.
Requires a sampling frame.
Variability in the characteristics of units is not very large.
Initially, the 4th employee is selected and then every 5th employee is selected.
StratifiedRandom selection of the units from the sub-population formulated based on the variability in the characteristics of the population. This selection from strata (groups) could be proportional or non-proportional.Suitable for populations having variability in characteristics.
Applicable when the researcher has limited time and money.
A sampling frame is required.
Division of employees on the basis of gender first, and then selecting them randomly.
ClusterCategorization of the very large population in different clusters (groups) based on their geographical area or any other feature.Suitable for a large population.
Applicable when the researcher has limited time and money.
Suitable when the entire population can be divided into clusters based on some common feature like geographical area.
Dividing the employees into clusters based on geographical location and then selecting the clusters randomly.
Table 1: Probability-based Quantitative research sampling methods
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Non-probability sampling method

Non-probability-based quantitative research sampling method involves non-random selection of the sample from the entire population. All units of the population do not an equal chance of participating in the survey. Therefore, the results cannot be generalized for the population.

The non-probability technique of sampling is based on the subjective judgement of the researcher. Hence this method can be applied in cases wherein limited information about the population is available. Moreover, it requires less time and money. Non-probability sampling method can be of four types as shown below.

Figure 2: Types of non-probability sampling
Qualitative Research Sampling MethodSampling TypeMeaningApplicableExample
Non-Probability Sampling MethodConvenienceSelection of units which are convenient for the researcher to approach.Suitable for a large population.
Requires less time and money.
Don’t need to generalize the results.
A study is done to know the perception of the Delhi NCR people about the cleanliness initiatives by the government. A sample of 200 people living nearby is collected.
PurposiveSample for the study is selected based on the perception or knowledge or judgement of the researcher about the required sample set. Thus, sample units are handpicked from the population.Suitable for a large population who are difficult to reach.
Preferred when the researcher has less time and money.
A study needs to be done for knowing the perception of people about women empowerment. Thus, 100 females’ students from the nearby institution were approached and included in the study as the sample units.
QuotaSelection of the sample units from the different categories of people (male, female, youngsters, teenagers, or adult) formulated in the population-based on certain criteria (quota). These categories are defined as per researcher view on traits, features, or interest. Herein, the sample is selected from each category.Applicable when different characteristics are present in population i.e. groups could be formulated from the population.
Preferred when the researcher has less time and money.
A study is done for collecting reviews of people about the cosmetic brand. Two categories are defined by the researcher i.e. male and female. Thus, placing a quota that the sample unit should be between 25-45 years, the sample of 100 people is selected.
Snowball Selection of the sample units based on the network formulated by connecting with more units form the population. Herein, approached unit suggest researcher the other units which could be included in the study.Applicable when targeted population is very less Suitable when difficult to identify or locate a targeted population.
Suitable in the case when targeted population are not willing to disclose themselves.
Preferred when researcher has less time and money.
A study is done based on the difficulties faced by undocumented immigrants. Thus, the researcher approach one such immigrant and by the help of him/her approach other immigrants for collecting information.

Table 2: Non-probability-based Quantitative research sampling method

The results of the quantitative research are mainly based on the information acquired from the sample. An effective sample yields a representable outcome. To draw valid and reliable conclusions, it is essential to carefully compute the sample size of the study and define the sampling technique of the study.


Priya is the co-founder and Managing Partner of Project Guru, a research and analytics firm based in Gurgaon. She is responsible for the human resource planning and operations functions. Her expertise in analytics has been used in a number of service-based industries like education and financial services.

Her foundational educational is from St. Xaviers High School (Mumbai). She also holds MBA degree in Marketing and Finance from the Indian Institute of Planning and Management, Delhi (2008).

Some of the notable projects she has worked on include:

  • Using systems thinking to improve sustainability in operations: A study carried out in Malaysia in partnership with Universiti Kuala Lumpur.
  • Assessing customer satisfaction with in-house doctors of Jiva Ayurveda (a project executed for the company)
  • Predicting the potential impact of green hydrogen microgirds (A project executed for the Government of South Africa)

She is a key contributor to the in-house research platform Knowledge Tank.

She currently holds over 300 citations from her contributions to the platform.

She has also been a guest speaker at various institutes such as JIMS (Delhi), BPIT (Delhi), and SVU (Tirupati).


I am a master's in Economics from Amity University. Having a keen interest in Econometrics and data analysis, I was a part of the Innovation Project of Daulat Ram College, Delhi University. My core expertise and interest are in environment-related issues. Apart from academics, I love music and exploring new places.


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