Page 70 - Intermediate Statistics for Dummies

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Chapter 3
Building Confidence
and Testing Models
In This Chapter
Utilizing confidence intervals to estimate parameters
Testing models by using hypothesis tests
Finding the probability of getting it right and getting it wrong
Discovering power in a large sample size
ne of the major goals in statistics is to use the information you collect
Ofrom a sample in order to get a better idea of what’s going on in the
entire population you’re studying (because populations are generally large
and exact info is often unknown). The most common items to study are the
mean of the population, the proportion of the population that has a certain
characteristic, or a comparison of the means or proportions from two differ-
ent populations. These unknown values that summarize the population are
called population parameters. Researchers typically either want to get a
handle on what those parameters are, or they want to test a hypothesis
about the population parameters. In introductory statistics, you typically go
over confidence intervals and hypothesis tests for one and two population
means and one and two population proportions. Your instructor hopefully
emphasized that no matter which parameters you’re trying to estimate or
test, the general process is the same. If not, don’t worry; that’s what this
chapter’s all about.

The most important idea you can gain from this chapter is that intermediate
statistics focuses on building and testing models. You’re typically faced with
some random phenomena, and you’re trying to build a model that explains or
predicts that phenomena. The situation is more complex than it was in intro
stats, where you used one variable to predict another variable in simple
linear regression. Intermediate statistics takes it up a notch to using many
variables to predict another one. But as long as you keep the big picture of
how the process works in your mind, you’ll be okay.