Notes of Chapter 8 Hypothesis testing (8.2)

# Notes of Chapter 8 Hypothesis testing (8.2) - Chapter 8...

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Chapter 8 Hypothesis testing (8.2) Learning objectives and outcomes After this chapter, students will Understand null and alternative hypotheses Understand the test statistic and p-value Be able to calculate the test statistic and p-value Understand the decision rule and how to explain the decision Understand the significance level 1. Logic of hypothesis testing Definition of hypothesis test: A hypothesis test (or test of significance) is a procedure for testing a claim about a property of population. For example, test whether the proportion of smokers in the U.S. is 80%. Note: there is no way that we can survey every individual in the U.S., therefore we will take a sample and use the sample statistic to make an inference to the population proportion. Definition of null and alternative hypothesis and p-value: Null hypothesis (H 0 ): statement that the value of a population parameter (such as mean or proportion) is equal to a value. Alternative hypothesis (H a ): statement that the value of a population parameter is <,> or the value in H 0. P-value: Given H 0 is true, the probability of observing the current statistic or more extreme values. H 0 : p=0.8

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2. Test about a proportion (five steps of hypothesis testing) On page 385 of the book, the P-value method was summarized into 8 steps. But the first 4 steps are all about formulating the null and alternative hypothesis. The significance level is usually selected by a given problem, and it is usually 0.05 if not indicated in the problem. Therefore, in this notes, the steps of
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