Statistics Workbook For Dummies with Online Practice by Deborah J. Rumsey

Author:Deborah J. Rumsey
Language: eng
Format: epub
ISBN: 9781119547686
Publisher: Wiley
Published: 2019-04-16T00:00:00+00:00

Evaluating Confidence Interval Results: What the Formulas Don’t Tell You

When data comes from well-designed surveys and experiments, and is based on large random samples, you can feel good about the quality of the information. When the margin of error of any confidence interval is small, you assume that the confidence interval provides an accurate and credible estimate of the parameter. This isn’t always the case, however. Why not? Because not all data come from well-designed surveys and experiments and are based on large random samples.

When it comes to margin of error, less may be more. The formulas don’t realize it when the numbers plugged into them are based on biased data, so you have to spot those situations and disregard the seemingly precise results.

See the following for an example of when a reported margin of error is meaningless.

Q. Suppose that a survey on a popular Internet website receives responses from 50,000 people. The reported margin of error for this survey, according to the formula, is about 0.0045, or 0.45 percent, which is tiny. Is this margin of error correct? Explain. Assume that the calculations are correct.

A. According to the formulas, the mathematics may be correct, but the results are based on biased data and are therefore bogus. Basically, all Internet polls are bogus except those that actually go out and select their participants at random from the population. And that is impossible to do with a general population because many folks don’t use computers or go online.

13 Does margin of error measure bias?

14 Suppose that a margin of error isn’t reported. Should you automatically assume that it has a small value and move on?

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