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In the case of a single population the null

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Unformatted text preview: a Conclusion We use the evidence from the Step 3 to make a conclusion about the claim we are testing. We will also look at Step 4 in the next lesson. NEXT STEPS: DETERMINING THE HYPOTHESES In order to test a claim about population parameters, we create two opposing hypotheses. We call these hypotheses the null hypothesis, abbreviated H0, and the alternative hypothesis, abbreviate Ha. These hypotheses are statements about the population parameter(s) we are examining. The null hypothesis is the basis for our test. In Module 7 we examined sampling distributions of sample proportions. Each sampling distribution is defined by its population parameter, as well as the sample size. For example, a sampling distribution of sample proportions is defined by the population proportion. In the case of a single population, the null hypothesis states that the population proportion, or population mean, is equal to a specific value. In the case of two populations, the null hypothesis states that the population proportions, or population means, are equal to each other. We will use this equality to create the sampling distribution that will help us assess the evidence from the sample data. We often think of the null hypothesis as meaning no change, no difference, or no effect. The alternative hypothesis comes from the claim in the research question and is an inequality. For a single population, the alternative hypothesis states that the population proportion or population mean is greater than, less than, or not equal to the value in the null hypothesis. For two populations, the alternative hypothesis states that the population proportion (or population mean) for the first population is greater than,...
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