In This Chapter

Introducing hypothesis tests

Testing hypotheses about means

Testing hypotheses about variances

Whatever your occupation, you often have to assess whether something out of the ordinary has happened. Sometimes you start with a sample from a population about whose parameters you know a great deal. You have to decide whether that sample is like the rest of the population or if it's different.

Measure that sample and calculate its statistics. Finally, compare those statistics with the population parameters. Are they the same? Are they different? Does the sample represent something that's off the beaten path? Proper use of statistics helps you decide.

Sometimes you don't know the parameters of the population you're dealing with. Then what? In this chapter, I discuss statistical techniques and worksheet functions for dealing with both cases.

A *hypothesis* is a guess about the way the world works. It's a tentative explanation of some process, whether that process is natural or artificial. Before studying and measuring the individuals in a sample, a researcher formulates hypotheses that predict what the data should look like.

Generally, one hypothesis predicts that the data won't show anything new or interesting. Dubbed the *null hypothesis* (abbreviated H_{0}), this hypothesis holds that if the data deviate from the norm in any way, that deviation is due strictly to chance. Another hypothesis, the *alternative hypothesis ...*

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