Interpreting Power  For the sample data in Example 1 “Adult Sleep” from this section, Minitab and StatCrunch show that the hypothesis test has power of 0.4943 of supporting the claim that μ  < 7 hours of sleep when the actual population mean is 6.0 hours of sleep. Interpret this value of the power, then identify the value of β  and interpret that value. (For the t test in this section, a “noncentrality parameter” makes calculations of power much more complicated than the process described in Section 8-1, so software is recommended for power calculations.)

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Interpreting Power  For the sample data in Example 1 “Adult Sleep” from this section, Minitab and StatCrunch show that the hypothesis test has power of 0.4943 of supporting the claim that μ  < 7 hours of sleep when the actual population mean is 6.0 hours of sleep. Interpret this value of the power, then identify the value of β  and interpret that value. (For the t test in this section, a “noncentrality parameter” makes calculations of power much more complicated than the process described in Section 8-1, so software is recommended for power calculations.)

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