When do sampling errors occur

This can have adverse effects such as untimely data collection, lack of relevant inputs and poor quality research. A study wishes to examine the online subscriptions that people have in order to identify what prompts them to pay for such subscriptions and how the services offered by such platforms differ from others that they choose not to pay for.

The research includes options such as Amazon, Flipkart, Big basket, Hotstar, Netflix, Paytm mall etc and allows the respondent to mention any other names that have not been provided in the options. The targeted respondents for such studies are individuals that pay for such subscriptions. Sampling error can easily occur in such studies when the people that volunteer are majorly the customers of any one or two of the platforms mentioned above.

This seriously hinders the quality of research as:. This is a simple example of sample frame error and how it adversely affects research results.

Increasing the sample size can help incorporate more ideas and inputs into the study, making it more representative. Secondary resources of data published by other researchers help in getting insights that support accurate data collection. Random sampling provides an equal opportunity for every individual from the target population to be included into the target population. This division allows narrow research to take place that studies each segment as a separate and makes note of variations that arise among different groups , resulting in a nuanced research procedure.

Explore Voxco Survey Software. Hypothesis Transform your insight generation process Use our in-depth online survey guide to create an actionable feedback collection survey process. How to Increase Your Brand Awareness? In mark What is Controlled Experiment?

Transform your insight generation process Use our in-depth online survey guide to create an actionable feedback collection surv Voxco has a team of loyal survey software professionals. Respondent bias is covered in more detail below. Processing Errors There are four stages in the processing of the data where errors may occur: data grooming, data capture, editing and estimation.

Data grooming involves preliminary checking before entering the data onto the processing system in the capture stage. Inadequate checking and quality management at this stage can introduce data loss where data is not entered into the system and data duplication where the same data is entered into the system more than once.

Inappropriate edit checks and inaccurate weights in the estimation procedure can also introduce errors to the data. To minimise these errors, processing staff should be given adequate training and realistic workloads. Misinterpretation of Results This can occur if the researcher is not aware of certain factors that influence the characteristics under investigation.

A researcher or any other user not involved in the collection stage of the data gathering may be unaware of trends built into the data due to the nature of the collection, such as it's scope. Researchers should carefully investigate the methodology used in any given survey. Time Period Bias This occurs when a survey is conducted during an unrepresentative time period.

For example, if a survey aims to collect details on ice-cream sales, but only collects a weeks worth of data during the hottest part of summer, it is unlikely to represent the average weekly sales of ice-cream for the year.

Minimising Non-Sampling Error Non-sampling error can be difficult to measure accurately, but it can be minimised by careful selection of the time the survey is conducted, using an up-to-date and accurate sampling frame, planning for follow up of non-respondents, careful questionnaire design, providing thorough training for interviewers and processing staff and being aware of all the factors affecting the topic under consideration.

The main sources of error relating to respondents are outlined below. Sensitivity If respondents are faced with a question that they find embarrassing, they may refuse to answer, or choose a response which prevents them from having to continue with the questions.

For example, if asked the question: "Are you taking any oral contraceptive pills for any reason? Fatigue Fatigue can be a problem in surveys which require a high level of commitment from respondents. For example, diary surveys where respondents have to record all expenses made in a two week period. In these type of surveys, the level of accuracy and detail supplied may decrease as respondents become tired of recording all expenditures.

The proportion of these non-respondents in the sample is called the non-response rate. Non-response can be either partial or total. It is important to make all reasonable efforts to maximise the response rate as non-respondents may have differing characteristics to respondents. This causes bias in the results. Partial Non-Response When a respondent replies to the survey answering some but not all questions then it is called partial non-response. Partial non-response can arise due to memory problems, inadequate information or an inability to answer a particular question.

The respondent may also refuse to answer questions if they find questions particularly sensitive, or have been asked too many questions the questionnaire is too long. Total Non-Response Total non-response can arise if a respondent cannot be contacted the frame contains inaccurate or out-of-date contact information or the respondent is not at home , is unable to respond may be due to language difficulties or illness or refuses to answer any questions.

When conducting surveys it is important to collect information on why a respondent has not responded. For example when evaluating a program a respondent may indicate they were not happy with the program and therefore do not wish to be part of the survey.

Another respondent may indicate that they simply don't have the time to complete the interview or survey form. If a large number of those not responding indicate dissatisfaction with the program, and this is not indicated in the final report, an obvious bias would be introduced in the results. Minimising Non-Response Response rates can be improved through good survey design via short, simple questions, good forms design techniques and explaining survey purposes and uses. Assurances of confidentiality are very important as many respondents are unwilling to respond due to a fear of lack of privacy.

Targeted follow-ups on non-contacts or those initially unable to reply can increase response rates significantly. Following are some hints on how to minimise refusals in a personal or phone contact: Find out the reasons for refusal and try to talk through them Use positive language State how and what you plan to do to help with the questionnaire Stress the importance of the survey Explain the importance of their response as a representative of other units Emphasise the benefits from the survey results, explain how they can obtain results Give assurance of the confidentiality of the responses Other measures that can improve respondent cooperation and maximise response include: Public awareness activities including discussions with key organisations and interest groups, news releases, media interview and articles.

This is aimed at informing community about the survey, identifying issues of concern and addressing them. Advice to selected units by letter, giving them advance notice and explaining the purposes of the survey and how the survey is going to be conducted. Psychology Biology Physics Medicine Anthropology.

Don't miss these related articles:. Back to Overview "Sampling". Next Article » "Random Sampling Error". Full reference:. Related articles Related pages:. Random Sampling Error What is Sampling? Population Sampling. Want to stay up to date? Follow us! Follow ExplorableMind. Save this course for later Don't have time for it all now? No problem, save it as a course and come back to it later.

Add to my courses. Footer bottom Links. The Research Council of Norway. This project has received funding from the European Union's Horizon research and innovation programme under grant agreement No