Part IV

Guesstimating and Hypothesizing with Confidence

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In this part

Anytime you're given a statistic by itself, you haven't really gotten the full story. The statistic alone is missing the most important part: by how much that statistic is expected to vary. All good estimates of population parameters contain not just a statistic but also a margin of error. This combination of a statistic plus or minus a margin of error is called a confidence interval.

Now suppose you're already given a claim, assumption, or target value for the population parameter, and you want to test that claim. You do it with a hypothesis test based on sample statistics. Because sample statistics will vary, you need techniques that take this into account.

This part gives you a general, intuitive look at margin of error, confidence intervals, and hypothesis tests: their function, formulas, calculations, influential factors, and interpretation. You also get quick references and examples for the most commonly used confidence intervals and hypothesis tests.

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