During survey research, there is a factor called ‘Margin of Error’ to consider. It is essential while data analysis and defining a statistically significant survey result. This irritating error is omnipresent during research and this observable fact is also termed as ‘Confidence Intervals’. The researchers need to keep the margin of error level as low as possible. It is because you cannot gather responses that represent the entire population involved in your study. Here, the variable margin of research reveals to the researchers the amount of survey result that represents the target population’s views.
Margin of error
It is a metric that reveals an error in the survey results, especially in a study that depends on random sampling size. It shows the amount, which the researchers can anticipate the survey results to reveal from the overall studied population’s views.
It is vital to keep the margin of error as low as possible because a high one will be unable to reflect the target population’s genuine views on the survey results. A high margin of error reduces the reliability and trustworthiness of your survey. It cannot be employed in statistical surveys like quantitative, qualitative, or descriptive research. A low margin of error denotes a high confidence level in the accuracy of survey results and vice versa.
How to calculate margin of error?
Use the Margin of Error Calculator by OvationMR. You will need few variables to plug in the formula – sample size, population size, and confidence level.
- Population size – Determine the target population, which your survey results will represent.
- Sample size – It represents the response number acceptable by the researcher. [increase in sample size = decrease in margin of error] Use sample size calculator available on Ovation MR Platform.
- Confidence level – Define how acceptable your conclusions can be made based on collected data. You can attain this from the Z score table because the confidence level is equivalent to the odds of Z score. [Increase in confidence level = increase in margin error]. 98% confidence level means you are 98% sure that your sampling represents the target population.
Best practices to diminish the margin of error
A more consistent study is useful and there are fewer hindrances to struggle with. Here are a few best practices to apply in survey research and reduce confidence level interval or margin of error.
Reduce data variability
Less data variation allows estimating a boundary surrounding the population more accurately. Reduction in variability narrows the standard deviation causing the margin of error to lessen.
Solution – Change data collection methods like make the process more orderly or make precise measurements.
Enlarge sample size
A large sample size offers more observation opportunities and this creates a small interval around sample statistics.
Remember – A large sample size will need more resources and more time.
Use low confidence level
A low confidence level offers a more precise margin of error. Unfortunately, this action will have less confidence in determining the necessary population boundary.
Solution – Lower confidence level only if a more precise margin of error offsets the disadvantage of low confidence level. For example, if sample size increase seems expensive then lower confidence level to reduce the margin of error but always remember that confidence level has decreased.
The margin of error is a variable that cannot be totally diminished, but you can determine a close to accurate statistically sound survey result.