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Chapter 13: Confidence Intervals: Making Your Best Guesstimate
                                                    one doing karaoke at some point). This may create some bias in the results.
                                                    (The last time I was in Vegas, I believe I really saw Elvis; he was driving a van
                                                    taxi to and from the airport. . . .)
                                                    Notice that you could get a negative value for
                                                                                                . For example, if you had

                                                    switched the males and females, you would have gotten –0.19 for this differ-
                                                    ence. That’s okay, but you can avoid negative differences in the sample pro-
                                                    portions by having the group with the larger sample proportion serve as the   213
                                                    first group (here, females).
                                         Spotting Misleading Confidence Intervals
                                                    When the MOE is small, relatively speaking, you would like to say that these
                                                    confidence intervals provide accurate and credible estimates of their param-
                                                    eters. This is not always the case, however.
                                                    Not all estimates are as accurate and reliable as the sources may want you to
                                                    think. For example, a Web site survey result based on 20,000 hits may have a
                                                    small MOE according to the formula, but the MOE means nothing if the survey
                                                    is only given to people who happened to visit that Web site.

                                                    In other words, the sample isn’t even close to being a random sample (where
                                                    every sample of equal size selected from the population has an equal chance
                                                    of being chosen to participate). Nevertheless, such results do get reported,
                                                    along with their margins of error that make the study seem truly scientific.
                                                    Beware of these bogus results! (See Chapter 12 for more on the limits of
                                                    the MOE.)

                                                   Before making any decisions based on someone’s estimate, do the following:
                                                     ✓ Investigate how the statistic was created; it should be the result of a sci-
                                                        entific process that results in reliable, unbiased, accurate data.
                                                     ✓ Look for a margin of error. If one isn’t reported, go to the original source
                                                        and request it.
                                                     ✓ Remember that if the statistic isn’t reliable or contains bias, the margin
                                                        of error will be meaningless.

                                                    (See Chapter 16 for evaluating survey data and see Chapter 17 for criteria for
                                                    good data in experiments.)
















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