Most Common Survey Errors in Research and How to Avoid Them

There is iota of doubt that data is valuable. It offers deep insights into past events and future predictions, making it an essential resource of social & economic understanding. Nevertheless, data can be proved useful only if they are accurate and reliable. 

In research, especially in social science field, survey is considered as the best approach utilised for collecting information from  pre-defined group of respondents. This method has various purposes and is performed depending on the chosen methodology. Typically, a survey includes data collection via questionnaires, QR codes, Emails, or other social networks. 

Some of the common types of survey designs used in research are:

• Cross-sectional survey design – Here, the data is collected at one point of time. 
• Longitudinal survey design – In this type of survey, the data is collected for prolonged period. 
• Cohort studies – This type of survey involves selection of sub-population and then collecting the data. 
• Panel studies – Here, the researcher observes the same population over time.

Besides emphasizing surveying practices, it is a must to make judgements on the factors that affect the survey process. This is because even though the reliable statistical tools is implemented to produce the best random samples, a researcher would still come across errors that impact the entire data collection & analysis process. 

Survey error is inevitable when getting a sample, therefore taking ‘g’ error is a must when collecting a sample so as to take measures to estimate and reduce the sampling error. 

Note that the margin of error that we witness with survey outcomes is an estimation of sampling error. 

Common Types of  Survey Errors

1. Accidental errors  – As the name suggests, accidental errors are the result of factors that are beyond the control of the researcher. Put simply, this type of surveying errors occur due to the unavoidable situations such as variations in the atmospheric conditions, etc. In addition, errors in survey as a result of imperfection in the measuring tools or techniques fall in this survey error category. The errors may be positive or may change the sign, but it cannot be accounted for the process. 
2. Mistakes – This type of survey errors arise due to inexperience, inattention, poor judgement or carelessness of the researcher. Mistakes do not follow the law of probability or any mathematical rule. It can be large or small, negative or positive but cannot be measured. However, it can be detected by performing the whole procedure on repeatedly. If a mistake goes undetected, it can affect the final outcome of the data analysis process. Therefore, every value should be thoroughly checked by independent field observer. 
3. Systematic errors – Systematic error, also known as cumulative error, in an error which are of the same size and size under the same conditions. This type of error follows definite physical or mathematical law. As a result, a solution can be identified and applied. Systematic errors can be positive or negative and have an impact on the final outcome of the analysis process. I.e., they make the result large or small. These errors arise due to number of reasons such as leveling of instrument, temperature, and many more. 
4. Compensating errors – This kind of error occurs in both directions, i.e., in negative as well as positive direction, thereby compensating each other. This type of error follows mathematical laws of probability and hence can be solved by determining the apt solution. 

Some of the possible ways to avoid survey errors and make the most out of it include:

1. Keep your survey question easy and directing to the purpose of your study. 
2. Lengthy questionnaires distract the respondents making them answering the questions randomly. Keep the questionnaire compenshive and short (minimum questions ) which can be answered within a few minutes.
3. The main intent of getting open ended questions is to understand the mindset and thoughts. Don’t use too many open ended questions making the respondents feel like they are writing essays instead of filling up the questionnaire. 
4. Use similar type of questions by using likert scale making. It’s easy for respondents to give valuable feedback in one go by using rating scale.
5. Pass your questionnaire across lot many respondents to make the sample size sufficiently large as it will make the study more effective.
6. Use digital platform to create survey to increase the ease of filling and giving some additional feedback and coupons codes to increase the responsive of the respondents.
7. Perform pre-testing for all the questionnaires

All in all, surveys can be a comprehensive tool to help you collect precise data! Avoid the above-mentioned errors and place your study on the way to its success!

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