Research Ethics

Doing the right thing will not necessarily bring success but compromising the ethics almost leads to failure.

Ethics are basic principle which shows  how an activity should be conducted. Ethics are crucial in research as it supports collaboration which is really important in scientific research.

Ethics and research go hand in hand as ethics define those moral ideals and principles that a person must follow, irrespective of the place or time of doing the research. Research ethics focus on the ethos and moral principles that a researcher must follow no matter which field of research they are working in.

Research follows scientific and systematic process and ethics should be followed in each at every step.


Ethics in Selection of Research Problem

A research problem is defined as the problem in which researcher is interested in and wants to explore its dimensions. Following are the ethics to be considered while deciding on research topic:

  • Subject which is overdone and is controversial should not be chosen. It should be interesting and unique.
  • One should not keep the research problem too narrow or too vague. It should always be specific.
  • It should be feasible to be carried out by the researcher in a defined time span. It should not take years and years to complete the research.
  • The variables chosen for the research should be measurable or observed.
  • Research topic should not be copied from other’s work unless there is really a good scope of improvement in existing work. If so, the results obtained from the research should be highly significant.
  • One should always check the importance of the research topic for its relevance in current scenario.


Ethics in Literature Review

A literature review is a comprehensive summary of previous research on a topic. The literature review surveys, enumerates, describes, summarizes, objectively evaluates and clarifies the previous research and work concluded by them. Many people do not understand it properly and take it lightly when it comes to do ethical literature review.

There are certain things to be taken care of while writing a literature review:

  • The secondary data that a researcher collects should be truthful and stated as given.
  • In-text citation is crucial when taking other’s work into research work.
  • Proper credit should be given to the researcher for extracting data from their research.
  • Researcher should have respect for Intellectual Property rights such as patents, copyrights and other intellectual property. While writing literature review, one should make sure that it is paraphrased properly, else it is considered as plagiarized content. One should check the plagiarism score of their work and it should not be more than 20%. It is important to ensure that there is no violation of any IP rights during research work as it is unethical.


Ethics in Research Design

This includes research problem, objectives, research method, sampling method, sample size, data collection, hypothesis and statistical tools for research. This should be written before you start the actual data collection. Generally, students at graduation and post graduation level, tend to waiver the research design after it is completed which is ethically incorrect. Most of the time changes are made in the sample size and statistical tools. To avoid it, the researcher should have prior in-depth knowledge about the research study that he is going to conduct. This will then provide clarity in deciding objectives, research method and research problem. For choosing a good sample size, appropriate methods of calculating sample size should be used.


Ethics in Sampling

To be ethical while conducting research, it is important for researcher to  be aware about the bias/errors.

A small error can ruin your research output. Lets quickly look upon the errors:-

Types of Errors

Sampling Error

Errors in research starts even before the data is collected. This is Sampling error, which refers to bias while selecting the respondents. This error occurs when only a part of the population is selected for research. Regardless of taking the best representative sample for research, there is always difference in the results of  population and the sample selected. The difference between the parameter and the estimates of the sample is known as sampling errors.

The sampling error may occur due to one or all of the following reasons:

  • Frame error: This error occurs when wrong sample is being taken from the population. For example, the survey is on the performance of luxury cars. Now the sample selected includes the individuals who have never used luxury cars. This creates an error and it will also effect the responses and the results derived from it.
  • Chance error: It is the difference between the expected(Population) value and the estimated(Sample)value. It is generally denoted by Standard error.
  • Response error: Such error occur due to many reasons 1) when only interested participants respond. 2) biased or faulty measurements 3) inaccuracy of survey instruments.



It can surely be mitigated by taking a larger sample or by using random sampling. It will also help in reducing the bias.


Non-Sampling Error

These are the error that occurs apart from the selection of sample. For instance, data collection error, interpreting error, data analysis error, respondent error etc.


Non-Sampling Error


Non Response error: It occurs when selected respondents choose not to respond

Response error: It is linked with all the errors that are connected to the way the response is getting collected.

  • Researcher error: The types of researcher errors are as follows:-
    • Surrogate Information error – These types of error occurs when there is difference in the actual information needed for the problem identified and the information collected by the researcher. For example : A survey is conducted to find the top beverages in the market. The option given by the researcher are Coca-cola, Pepsi and Fanta. But in reality there are many other option in beverage category. These type of research measure the preference of respondents over only 3 beverages mentioned rather than finding the top beverages. The best possible to avoid such error is to have few open ended question.
    • Population definition error – These type of error occurs when there is a difference between the actual population for the problem identified and the population taken by the researcher. To avoid such error, researcher should have clarity about the research problem and should be able to describe the exact population for the same. He can discuss with other people to avoid any bias.
    • Data analysis error – Such error occur while converting the raw data into findings and conclusion. The reason for such error is due to inadequate knowledge about the statistical tools. To avoid such kind of problem, researcher should first finalize the data analysis strategy before collecting data from respondents. It will not only help in mitigating data analysis error but also it will help in creating accurate questions for the respondents.


  • Interviewer error: The types of interviewer errors are as follows:-
    • Question error – The way question are asked or prepared is not proper. This inaccuracy occurs when the interviewer takes pauses or focus on certain words while asking the question. Generally, interviewer unintentionally or sometimes, intentionally ask leading and double-barrelled questions to get the desirable answers from the respondent. Also, in case of missing data, there are researchers who do data fudging, which means that they make data on their own rather than going to the field and collecting it.
    • Recording error – It occurs when the quality of either sound or video is not good. It creates problem for the researcher to interpret the answers properly.
    • Selection of respondents – It occurs when the participants selected for the interview are not eligible for the same. This results into sampling error and leads to inaccurate results. For instance, you need to collect data of male individuals who are less than the age of 40 years, but due to some negligence, you interviewed few respondents that were above the age of 40.


  • Respondent error: The types of respondent errors are as follows:-
    • Inability error – These errors occur when respondent might not be in a position to answer you. You have asked a scientific question to an individual who is incapable of understanding it.
    • Unwillingness error – Many times it happens that people are not willing to answer because of their own personal issues. Researcher need to be very careful about that.

Also, researcher should have proper rationale behind using a particular sample size for his research. Although 385 is the standard normal sample size, but it can always be calculated using a proper rationale of proportion, mean or population size behind it.


Ethics in Data Collection Tool

In case researcher has selected questionnaire as a data collection tool, they should:

  • Avoid leading questions that prompts the answer to respondent in your favour.
  • Use language  that is understandable to the respondent. No scientific words or abbreviations should be used. It will lead to inaccurate answers.
  • Form questions that covers the research topic. Do not keep one-sided questionnaire. Start with some general questions than dive into the specific questions related to your research topic.
  • Hypothetical questions that embarrass the respondents should be avoided.
  • Avoid double-barreled questions. It will weaken your accuracy of answers.
  • Data collected or the personal records of the respondents is to be kept confidential and not shared publicly. While doing analysis, an individual’s name should not be mentioned as it violates privacy issues.


In case researcher has selected Interview as a data collection tool, then:

  • Take prior understanding of what kind of respondents are eligible for your research.
  • Interviewer should be aware about the research problem and have knowledge about all the question that he will be asking.
  • Questions should be asked in such a manner that it does not lead the respondent and it should be clear enough for him to understand.


Ethics in Data Analysis

This is the step where you code the data, apply the statistical tool and get results about whether the hypothesis is accepted or rejected. After the results are arrived, you analyze them and make conclusions from it. There are certain ethics to be followed during this process:

  • One should be honest while collecting data, reporting, analyzing results and selecting statistical tools for conducting research. Results should be ethically mentioned as per the output through data analysis. It should not be modified or interpreted according to researcher’s opinion or thought process.
  • Before selecting any tool (Anova, regression, T-test, F-test, correlation and chi-square) for the data analysis, researcher should be aware about the pre-requisites and why particular tool is being used. There are reasons behind using any statistical tools. For instance, Anova is used when you want to find the difference in the variances of between and within the variables, Chi- square is used to find whether the variables are independent or dependent of each other.
  • This is the most important thing to be followed, if not, it will reduce the reliability of your research resulting into type-I and type-II errors.


Ethics in Reporting Results

  • There are lot of bias that comes into picture unintentionally or intentionally while analyzing and concluding the results. Researcher should be more objective rather than subjective. He/she should  keep aside his emotions and perception. All the methods, data and output should be reviewed as given.
  • Researcher should be open in sharing the findings, ideas, resources used by him. He should be open to take criticisms and follow new ideas given by people.



While ending this discussion, being ethical in research is essential as it promotes the importance of collaboration, trust, accountability and fairness. It shows that the research work has:

Relevant information – It means that the content provided in the research is relevant with the research topic and it is applicable to current scenario.

Empirical evidence – All the information mentioned in the research paper should have empirical evidence i.e it should have proper documentation which can act as  proof for it.

Verifiability – The information should be observable/measurable. The content should be backed by empiricism. All evidence should be capable of being measured or observed.

Reliability – The content should be trustworthy and consistent throughout the research. It means that the results derived from the data should be reliable and consistent, regardless of being tested number of times with the same variables.

Validity – It measures the accuracy of your research result. Specifically, the design and the methods that you have selected should be valid. The findings of the research should represent the claims that you have made in your research.


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    By: Urvika Zalawadia

    Urvika Zalawadia is an inquisitive person and likes to read about new marketing trends. She has written research paper regarding Advertising appeals and Online streamers. She also has a keen interest in data analysis through SQL. She is passionate about acquiring knowledge related to marketing strategies.

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3 Responses to “Research Ethics”

  1. Akshay says:

    Carry on..don’t stop 💯

  2. Shikha Chandan says:

    Truly very beneficial post, as ethics are very important in conducting any research. Keep up with the good work.

  3. Archie Kanwar says:

    ThankYou! For providing a great knowledge of ethics in research. This would be really helpful for everyone..

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