activity sheet for hypothesis testing

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A useful website for preparation State the Hypotheses Every hypothesis test requires the analyst to state a null hypothesis and an alternative hypothesis . The hypotheses are stated in such a way that they are mutually exclusive. That is, if one is true, the other must be false; and vice versa. The table below shows three sets of hypotheses. Each makes a statement about how the population mean μ is related to a specified value M . (In the table, the symbol ≠ means " not equal to ".) Set Null hypothesis Alternative hypothesis Number of tails 1 μ = M μ ≠ M 2 2 μ > M μ < M 1 3 μ < M μ > M 1 The first set of hypotheses (Set 1) is an example of a two-tailed test , since an extreme value on either side of the sampling distribution would cause a researcher to reject the null hypothesis. The other two sets of hypotheses (Sets 2 and 3) are one-tailed tests , since an extreme value on only one side of the sampling distribution would cause a researcher to reject the null hypothesis. Formulate an Analysis Plan The analysis plan describes how to use sample data to accept or reject the null hypothesis. It should specify the following elements. Significance level. Often, researchers choose significance levels equal to 0.01, 0.05, or 0.10; but any value between 0 and 1 can be used. Analyze Sample Data Using sample data, conduct the test. This involves finding the standard error, degrees of freedom (only for t-test), test statistic, and the P-value associated with the test statistic. Degrees of freedom. The degrees of freedom (DF) is equal to the sample size (n) minus one. Thus, DF = n - 1.
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Interpret Results If the sample findings are unlikely, given the null hypothesis, the researcher rejects the null hypothesis. Typically, this involves comparing the P-value to the significance level
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This note was uploaded on 05/21/2011 for the course MARKETING 104 taught by Professor Fazli during the Spring '11 term at College of E&ME, NUST.

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activity sheet for hypothesis testing - A useful website...

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