Statistical margin of error

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Statistical margin of error

A statistical margin of error is used to express the amount of random sampling error in a research survey. Researchers will aim for a smaller margin of error as to increase the validity of their study and show they have sampled a good representation of the target population. Every research study will have a statistical margin of error, unless the study tests the whole of a target population.

The margin of error in statistics also relates to the confidence interval of a research study. The confidence interval is an estimate that the whole target population will fall between a certain range of data. They measure the degree of uncertainty in a sample population and will often estimate between 95% and 99% confidence – when a greater number of participants are observed, the percentage of confidence increases, therefore the confidence interval decreases. The statistical margin of error is equal to half of the confidence interval, meaning that when more people are tested, the margin of error decreases, leading to a more valid study.

If a survey is published without a margin of error specified, it could be viewed as incomplete. For example, if a research study stated that 29% of adults have cereal before work with an error margin of 4%, the data should be interpreted to be 25–33% of adults have cereal before work. Without the statistical margin of error, the data changes significantly and wouldn’t be an accurate representation of the whole target population.

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