In the media, numerous surveys are often displayed reporting percentages or proportions. A margin of error is often reported in the survey and this is used to calculate confidence intervals. Why is it important to create/report confidence intervals (CI) rather than just reporting the averages or proportions? is it better to use 95% confidence interval or 99% confidence interval?
The CI gives some indication of how accurate the data is. Do you believe the 4% difference is important?
Creating and reporting confidence intervals is important because it provides a range of values within which the true population parameter is likely to fall. This reflects the inherent uncertainty in any survey or study conducted on a sample of the population.
The margin of error is a measure of the uncertainty associated with the survey estimate. By calculating a confidence interval, we are able to communicate the level of uncertainty in the survey results. This is valuable because it helps users of the information to understand the range within which the true value is likely to lie. Without confidence intervals, it would be misleading to present a single point estimate without acknowledging the variability and potential error.
Now, regarding the choice between a 95% confidence interval and a 99% confidence interval, it ultimately depends on the level of certainty you require.
A 95% confidence interval means that if we were to repeat the survey or study many times, we would expect the resulting intervals to contain the true population parameter in 95% of those cases. This level of confidence is commonly used in many fields and is often considered sufficient.
On the other hand, a 99% confidence interval provides a higher level of certainty. It means that if we were to repeat the survey or study many times, we would expect the resulting intervals to contain the true population parameter in 99% of those cases. However, the trade-off is that a wider interval is needed since we are aiming for a higher level of confidence. This wider interval may reduce the precision of the estimate.
So, the choice between a 95% confidence interval and a 99% confidence interval depends on the context and the importance of minimizing uncertainty. If a higher level of confidence is desired, even at the cost of wider intervals, a 99% confidence interval may be preferred. However, if the standard level of confidence used in a particular field is 95%, a 95% confidence interval would suffice.