Limitations and weakness of quantitative research methods

By Priya Chetty on September 7, 2016

According to Saunders et al. (2009), research methodology serves as the backbone of a research study. Quantitative research’s main purpose is the quantification of the data. It allows generalisations of the results by measuring the views and responses of the sample population. Every research methodology consists of two broad phases namely planning and execution (Younus 2014). Therefore, it is evident that within these two phases, there are likely to have limitations which are beyond our control (Simon 2011). 

Improper representation of the target population

As mentioned in the article, improper representation of the target population might hinder the researcher from achieving its desired aims and objectives. Despite applying an appropriate sampling plan representation of the subjects is dependent on the probability distribution of observed data. This may lead to a miscalculation of probability distribution and lead to falsity in the proposition.


A study purports to check the proportion of females aged between 20-30 years who are applying make-up ranges of international brands. The target population, in this case, is the women belonging to the said age group, with both professional and non-professional backgrounds, residing in Delhi. The sampled population based on the probability distribution has to be calculated against the total females residing in the city (e.g. 400 sampled out of 7,800,615 female populations). However, there is a scope of getting partial information about the range of makeup products from the sampled, owing to its meagre form against the total population. Hence, the results of the study cannot be generalised in context to a larger population, but rather be suggested.

Lack of resources for data collection

Quantitative research methodology usually requires a large sample size. However, due to the lack of resources, this large-scale research becomes impossible. In many developing countries, interested parties (e.g., government or non-government organisations, public service providers, educational institutions, etc.) may lack knowledge and especially the resources needed to conduct thorough quantitative research (Science 2001).

Inability to control the environment

Sometimes researchers face problems to control the environment where the respondents provide answers to the questions in the survey (Baxter 2008). Responses often depend on a particular time which again is dependent on the conditions occurring during that particular time frame.


For example, if data for a study is collected on residents’ perception of development works conducted by the municipality, the results presented for a specific year (say, 2009), will be held redundant or of limited value in 2015. The reasons are, that either the officials have changed or the development scenario has changed (from too effective to minimal effective or vice versa).

Limited outcomes in a quantitative research

The quantitative research method involves a structured questionnaire with close-ended questions. It leads to limited outcomes outlined in the research proposal. So the results cannot always represent the actual occurrence, in a generalised form. Also, the respondents have limited options for responses, based on the selection made by the researcher.


“Does your manager motivates you to take up challenges”

The answer can be Yes / No / Can’t say or Strongly Agree to Strongly disagree. But to know what strategies are applied by the manager to motivate the employee or on what parameters the employee does not feel motivated (if responded no), the researcher has to ask broader questions which somewhat has limited scope in close-ended questionnaires

Expensive and time-consuming

Quantitative research is difficult, expensive and requires a lot of time to perform the analysis. This type of research is planned carefully in order to ensure complete randomization and correct designation of control groups (Morgan 1980). A large proportion of respondents is appropriate for the representation of the target population. So, to achieve in-depth responses on an issue, data collection in quantitative research methodology is often too expensive than the qualitative approach.


To understand the influence of advertising on the propensity of purchase decision of baby foods parents of 5-year old and below in Bangalore, the researcher needs to collect data from 200 respondents. This is time-consuming and expensive, given the approach needed for each of these parents to explain the study’s purpose.

Difficulty in data analysis

The quantitative study requires extensive statistical analysis, which can be difficult to perform for researchers from non-statistical backgrounds. Statistical analysis is based on scientific discipline and hence is difficult for non-mathematicians to perform.

Quantitative research is a lot more complex for social sciences, education, anthropology and psychology. The effective response should depend on the research problem rather than just a simple yes or no response.


To understand the level of motivation perceived by Grade 5 students from the teaching approach taken by their class teachers, mere yes and no might lead to ambiguity in data collection and hence improper results. Instead, a detailed interview or focus group technique might develop in-depth views and perspectives of both the teachers and children.

Offer ID is invalid

Requirement of extra resources to analyse the results

The requirements for the successful statistical confirmation of the result are very tough in quantitative research. A hypothesis is proven with few experiments due to which there is ambiguity in the results. Results are retested and refined several times for an unambiguous conclusion (Ong 2003). So it requires extra time, investment and resources to refine the results.


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  • Science, J. of D., 2001. Invited Review: Integrating Quantitative Findings from Multiple Studies Using Mixed Model Methodology. Journal of Dairy Science, 84(4), pp.741–755.
  • Simon, M.K., 2011. Dissertation and scholarly research: Recipes for success, Seattle, W.A.: Dissertation Success LLC.
  • Younus, M.A.F., 2014. Research Methodology. In Vulnerability and Adaptation to Climate Change in Bangladesh: Processes, Assessment and Effects (Springer Theses). Springer, pp. 35–76. Available at: [Accessed August 1, 2016].

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).



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