Chapter 13
Confidence Intervals: Making Your Best Guesstimate
In This Chapter
- Understanding confidence interval pieces, parts, and interpretation
- Calculating with confidence
- Examining factors that influence the width of a confidence interval
- Detecting misleading results
Most statistics are used to estimate some characteristic about a population of interest, such as average household income, the percentage of people who buy birthday gifts online, or the average amount of ice cream consumed in the United States every year (and the resulting average weight gain — nah!). Such characteristics of a population are called parameters. Typically, people want to estimate (take a good guess at) the value of a parameter by taking a sample from the population and using statistics from the sample that will give them a good estimate. The question is: How do you define “good estimate”?
As long as the process is done correctly (and in the media, it often isn't!), an estimate can often get very close to the parameter. This chapter gives you an overview of confidence intervals (the type of estimates used and recommended by statisticians); why they should be used (as opposed to just a one-number estimate); how to set up, calculate, and interpret the most commonly used confidence intervals; and how to spot misleading estimates.
Not All Estimates Are Created Equal
Read any magazine or newspaper or listen to any newscast, and you hear a number of statistics, many of which are estimates of some quantity ...
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