Statistical Sciences 2244A/B Chapter Notes - Chapter 7: Simple Random Sample, Binomial Distribution, Normal Distribution
5 Mar 2014
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Document Summary
This chapter describes the statistical procedure for testing hypotheses. The two major activities of inferential statistics are the estimation of population parameters and hypothesis testing. In statistics a hypothesis is a claim or statement about a property of a population. A hypothesis test (or test of significance) is a standard procedure for testing a claim about a property of a population. Recall the rare event rule for inferential statistics: If, under a given assumption, the probability of a particular observed event is exceptionally small, we conclude that the assumption is probably not correct. Following this rule, we test a claim by analyzing sample data in an attempt to distinguish between results that can easily occur by chance and results that are highly unlikely to occur by chance. In this section we describe the formal components used in hypothesis testing: null hypothesis, alternative hypothesis, test statistic, critical region, significance level, critical value, p-value, type i error, type ii error.
