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Hypothesis Testing (Tests of Significance) and
The one-sample Z test

Hypothesis Testing (Tests of Significance) and  The one-sample Z 03/04/2014

BIOL 280, Handout 11
Hypothesis Testing (Tests of Significance) and
The one-sample Z test
B&M pages 363-375, Homework problem 14.49 (due with Homework 3)

Confidence Intervals are appropriate when our goal is to estimate (make inferences about) a population parameter. Significance tests do something very different: they are a way to assess the evidence provided by the data regarding some claim (hypothesis) about the population. More specifically, they are a way of comparing observed data with a hypothesis about some characteristic of the greater population.

• The Hypothesis is a statement about some parameter of the population. It can take a number of different forms, which we will discuss.
• The results of the significance test of the hypotheses are expressed in terms of a probability (or p value) that measures how well the data and the hypothesis agree.

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